Methicillin resistant Staphylococcus aureus (MRSA) emerged long before the introduction of the antibiotic methicillin into clinical practice, according to researchers at the University of St Andrews.
A new study, in collaboration with the Wellcome Trust Sanger Institute and the University of Dundee, suggests the widespread use of earlier antibiotics such as penicillin rather than of methicillin itself allowed Methicillin resistant Staphylococcus aureus (MRSA) to emerge.
The findings, published in the open access journal Genome Biology, found that S. aureus acquired the gene that confers methicillin resistance (mecA) as early as the mid-1940s, fourteen years before the first use of methicillin.
Professor Matthew Holden, molecular microbiologist at the University of St Andrews, the corresponding author said:
“Our study provides important lessons for future efforts to combat antibiotic resistance. It shows that new drugs which are introduced to circumvent known resistance mechanisms, as methicillin was in 1959, can be rendered ineffective by unrecognized, pre-existing adaptations in the bacterial population. These adaptations happen because, in response to exposure to earlier antibiotics, resistant bacterial strains are selected instead of non-resistant ones as bacteria evolve.”
The mecA gene confers resistance by producing a protein called PBP2a, which decreases the binding efficiency of antibiotics used against S. aureus to the bacterial cell wall. The introduction of penicillin in the 1940s led to the selection of S. aureus strains that carried the methicillin resistance gene.
Dr Catriona Harkins, clinical lecturer in dermatology at the University of Dundee, the first author of the study said:
“Within a year of methicillin being first introduced to circumvent penicillin resistance, strains of S. aureus were found that were already resistant to methicillin. In the years that followed resistance spread rapidly in and outside of the UK. Five decades on from the appearance of the first MRSA, multiple MRSA lineages have emerged which have acquired different variants of the resistance gene.”
To uncover the origins of the very first MRSA and to trace its evolutionary history, the researchers sequenced the genomes of a unique collection of 209 historic S. aureus isolates. The oldest of these isolates were identified over 50 years ago by the S. aureus reference laboratory of Public Health England and have been stored ever since in their original freeze-dried state. The researchers also found genes in these isolates that confer resistance to numerous other antibiotics, as well as genes associated with decreased susceptibility to disinfectants.
Professor Holden said:
“S. aureus has proven to be particularly adept at developing resistance in the face of new antibiotic challenges, rendering many antibiotics ineffective. This remains one of the many challenges in tackling the growing problem of antimicrobial resistance. In order to ensure that future antibiotics retain their effectiveness for as long as possible, it is essential that effective surveillance mechanisms are combined with the use of genome sequencing to scan for the emergence and spread of resistance.”
St Andrews is made up from a variety of institutions, including three constituent colleges (United College, St Mary’s College, and St Leonard’s College) and 18 academic schools organised into four faculties. The university occupies historic and modern buildings located throughout the town. The academic year is divided into two terms, Martinmas and Candlemas. In term time, over one-third of the town’s population is either a staff member or student of the university. The student body is notably diverse: over 120 nationalities are represented with over 45% of its intake from countries outside the UK; about one-eighth of the students are from the rest of the EU and the remaining third are from overseas — 15% from North America alone. The university’s sport teams compete in BUCS competitions, and the student body is known for preserving ancient traditions such as Raisin Weekend, May Dip, and the wearing of distinctive academic dress.
richardmitnick
10:26 am on July 20, 2017 Permalink
| Reply Tags: Applied Research & Technology ( 4,291 ), Elizabeth Davis spent 21 years trying to receive a correct diagnosis from doctors about her condition which prevented her toes from uncurling causing her to walk with crutches for the most of her life, Genetics ( 101 ), Genomics ( 34 ), GTPCH1 impairs her ability to produce dopa, Medicine, Mutagenesis, NCGENES project, They were able to treat it — with something as simple as a pill. A pill that has been on the market since 1988 used to treat patients with Parkinson’s disease, UNC ( 10 )
Davis can now walk fully unsupported and live a relatively normal life thanks to a correct diagnosis from UNC researchers within the NCGENES project. No image credit.
“Consider this: In 1969, if a disease-linked gene was found in humans, scientists had no simple means to understand the nature of the mutation, no mechanism to compare the altered gene to normal form, and no obvious method to reconstruct the gene mutation in a different organism to study its function. By 1979, that same gene could be shuttled into bacteria, spliced into a viral vector, delivered into the genome of a mammalian cell, cloned, sequenced, and compared to the normal form.” —Siddhartha Mukherjee, “The Gene: An Intimate History”
“I can move my toes,” Elizabeth Davis says.
Her 9-year-old son looks at her in awe. The two stand, wide-eyed in the middle of a Verizon Wireless store in Goldsboro, North Carolina. Davis leans hard against her crutches, staring at her feet. She looks up and smiles.
At age 37 — for the first time in 31 years — Davis can uncurl her toes from a locked position, the symptom of a condition gone misdiagnosed for just as long. Three months later, she sheds her crutches, walking fully unsupported — something she hasn’t done since she was 14 years old.
In 1975, the same year Davis was born, UNC microbiologists Clyde Hutchison and Marshall Edgell experienced a different kind of life-changing event. They’d been working rigorously to isolate DNA within the smallest-known virus at the time, Phi-X174. More than anything, they wanted to understand how to read the genetic code. Then, later that year and across the pond at St. John’s College in Cambridge, Fred Sanger figured it out. The British biochemist became the first person to develop a relatively rapid method for sequencing DNA, a discovery that won him a Nobel Prize in Chemistry — for the second time.
In response to Sanger’s discovery, Hutchison took a sabbatical and headed to England to work in his lab. During his first year there, he helped uncover the entire sequence of Phi-X174 — the first time this had been done for any organism. While there, he realized the new ability to read DNA could help him and Edgell solve a different problem they’d been having back in North Carolina: fusing two pieces of DNA code together to create an entirely different sequence.
After returning to Chapel Hill, Hutchison continued his work with Edgell and also Michael Smith, a researcher at the University of British Columbia who he met while working in Sanger’s lab. Together, the trio successfully fused two differing DNA strands using a more flexible approach to site-directed mutagenesis — a technique that makes gene therapy possible today. They published their results in 1978. Smith would go on to receive the Nobel Prize for this work in 1992.
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The scientific breakthroughs of the 1970s changed the field of genetics forever. In 1980, Sanger received the Nobel Prize for Chemistry for his contributions, along with Walter Gilbert (Harvard), who discovered that individual modules from different genes mix and match to construct entirely new genes; and Paul Berg (Stanford), who developed a technique for splicing recombinant DNA.
Meanwhile, researchers in Chapel Hill continued to chip away at the mysteries of the gene. Oliver Smithies, who came to UNC in 1987, would later win the Nobel Prize for his work in gene targeting using mouse models. That same year, UNC cancer geneticist Michael Swift and team discover the AT gene, which predisposes women to breast cancer; and George McCoy becomes the first clinical trial participant in the world to receive the genetically engineered Factor VIII gene to treat his hemophilia at the then UNC-Thrombosis and Hemostasis Center.
Genetics was changing the world. And this was only the beginning.
An unsolved mystery
One year after Sanger won the Nobel Prize, Elizabeth Davis turned 6. She soon began walking on her toes, which had suddenly, one day, curled under in pain, making it nearly impossible for her to stride with feet flat on the ground. Her knees knocked together as she struggled to move with the swift pace characteristic of a child her age. Davis continued to walk on her toes for years.
“I would even brace the school walls when walking down the hallway,” she says. Eventually, the pain became unbearable. By the time she was 12, she’d resigned herself to crutches.
Doctors believed Davis’ condition could be treated with foot surgery, misdiagnosing her condition for years. By age 14, she had already undergone three procedures — two to lengthen her Achilles tendons and an experimental bone fusion. But each surgery offered little to no relief, and walking only grew more painful for Davis, both physically and emotionally. As her condition worsened, her classmates became cruel — so much so that she dropped out of high school when she was just 16.
By age 20, Davis grew restless. “The pain was constant,” she remembers. “I could hardly move my legs — they just felt weak. I would drag them behind me as I used my crutches. I couldn’t even lift them.” Doctors suggested she undergo a third Achilles tendon lengthening surgery, the result of which minimally improved her condition.
“By that age, I just wanted more,” Davis says. “I just wanted to do things, to go places. I wanted the surgery to work. But it didn’t. And the pain continued.”
It would be another 17 years before doctors realized the problem was hidden in her genome.
The birth of a department
In 1990, the start of the Human Genome Project — an international research program to map out the 20,000 genes that define human beings — further fueled new discoveries in the field of genetics. So when Jeff Houpt, then-UNC School of Medicine dean, formed a research advisory committee in 1997 and asked his faculty what the number-one research program the university needed to focus on, they responded: genetics and genome sciences.
Great minds think alike. At the same time, the College of Arts and Sciences was also hosting its own committee that vied to develop a genetics department. “At this point, I had a vision for a pan-university program,” Houpt shares. “This wasn’t just going to be a program of the medical school.”
Along with the College, the schools of public health, dentistry, pharmacy, nursing, and information and library science all wanted in, offering financial assistance to the program. Then-Provost Robert Shelton and Chancellor James Moeser both signed off on it as well. “What we wanted from Shelton and Moeser was more money and more positions,” Houpt remembers. “And they agreed to that.”
By 2000, a hiring committee was ready to interview candidates to chair the new department and genomics center. Terry Magnuson quickly emerged as the lead candidate. He and his team had spent the past 16 years researching developmental abnormalities using genetics and mouse models, successfully changing the genetic background of a mutated gene.
“It was obvious he was going to have a following,” Houpt remembers. “People were going to listen to him because he’s a good scientist. But more than that, it was pretty clear that Terry was interested in building a program, and this university-wide effort appealed to him.”
Unanswered pain
By the time she reached her 30s, Davis’ condition had spread to her arms. She underwent multiple MRIs, nerve and muscle testing, and a spinal tap. She even endured a fifth, unsuccessful surgery on her feet. Physicians misdiagnosed her yet again. A few believed she suffered from hereditary spastic paraplegia, a genetic condition that causes weakness in the legs and hips. Another told her she had cerebral palsy. “But I didn’t want to believe him,” she says — and it’s a good thing she didn’t.
As Davis continued her search for answers, walking grew more and more painful. “I was always in pain,” she admits. “But some weeks were really, really bad — to the point where I couldn’t even move.” She finally succumbed to the assistance of a wheelchair. “I hated it so much. I barely went anywhere.” And when she did, she needed help.
Her mother assisted her regularly with everyday tasks like grocery shopping. Her youngest son, Alex, learned to expertly navigate her around high school gyms, baseball fields, and the local YMCA pool so she could watch her other son, Myles, compete in the plethora of sports he participated in.
“Myles really experienced the worst of it,” Davis says. “I remember one time, in particular. I was taking a shower and knew I was about to fall. I called for him and he came running. He was always there to pick me back up.”
Sequences and algorithms
After the Human Genome Project published its results in 2004, genomic sequencing became an option for people with undiagnosed diseases. But analyzing and understanding the 3 billion base pairs that make up a person’s genetic identity was an expensive process. As time progressed and technology improved, though, the technique became more manageable for both physicians and patients.
Using these new genomic technologies for outpatient care intrigued UNC geneticists James Evans and Jonathan Berg. In 2009, after gathering enough preliminary data, the NIH granted the team the funds to start the North Carolina Clinical Genomic Evaluation by NextGen Exome Sequencing (NCGENES), which uses whole exome sequencing (WES) to uncover the root cause of undiagnosed diseases. Using just two tablespoons of blood, WES tests 1 percent of the genome — a feat that is both miraculous and controversial, creating a whole new wave of ethical questions.
Simply put: “Some people want information that other people don’t,” Evans explains. Most people want to know about genetic disorders that have treatment options, but when it comes to those that don’t, they’d rather not hear it. “Navigating those different viewpoints can be a challenge,” he says. Privacy and confidentiality also present problems within the insurance world. Although protections exist in the realm of medical insurance, major genetic predispositions could have large implications for life, disability, and long-term care insurance.
Today, upward of 50 researchers from across Carolina participate in NCGENES to study everything from the protection of data to the delivery of results. More than 750 people with undiagnosed diseases have undergone testing.
NCGENES wouldn’t exist without the technical infrastructure that tracks, categorizes, and helps analyze genetic material as it makes its way through multiple laboratories — all of which is provided by UNC’s Renaissance Computing Institute (RENCI). A developer of data science cyberinfrastructure, RENCI provides the software programming that helps the team at NCGENES analyze genomes more effectively.
“You need new computer algorithms to solve new science problems,” RENCI Director Stan Ahalt says. “It takes a multidisciplinary team to understand science problems like genetics — and computer code to make that process go fast.”
A transformative experience
By 2013, Davis was in desperate need of a new algorithm. Thankfully, that year, she was referred to Jane Fan, a pediatric neurologist at UNC. After studying Davis’ file, Fan felt sure that the doctors who tried to diagnose her condition failed, making her the perfect candidate for NCGENES.
Four tubes of blood, 100,000 possible genetic locations, and just over six months later, Fan called Davis. A single gene mutation called GTPCH1 impairs her ability to produce dopa, an amino acid crucial for nervous system function. “I had to hear it in person before I believed it,” Davis admits. “I had been misdiagnosed many times before.”
Not only were UNC geneticist James Evans and his NCGENES team finally able to accurately diagnose Davis, but they were able to treat it — with something as simple as a pill. A pill that has been on the market since 1988, used to treat patients with Parkinson’s disease.
And just like that, Davis ‘life was changed forever by genome sequencing.
Three days after she took one-quarter of a pill, movement returned to her toes while standing in the middle of a Verizon Wireless store in Goldsboro. She began to cry.
Top-five in the country
UNC’s genetics department has ranked in the top-five programs for NIH funding across the nation every year since 2012 (and top-10 each year since 2006). “I think we’ve built one of the best genetics departments in the country,” Magnuson says. In 2016 alone, genetics department faculty brought $38 million to Carolina.
Houpt agrees with Magnuson’s sentiment. “The genetics department is a great example of how universities should run,” he says. “People need to put aside their own interests and see what’s needed. Terry is a leader who’s made each school involved feel like it’s their program and not just a medical school program – which is why he’s now the vice chancellor for research.”
Today, more than 80 faculty members from across campus conduct world-recognized genetics research in multiple disciplines.
Ned Sharpless, for example, focuses on cancer. Most recently, the director of the UNC Lineberger Comprehensive Cancer Center lead a study that paired UNCseq — a genetic sequencing protocol that produces volumes of genetic information from a patient’s tumor — with IBM Watson’s ability to quickly pull information from millions of medical papers. A procedure much too intense and time-consuming for the human mind, this data analysis can help physicians make more informed decisions about patient care.
Another member of Carolina’s Cancer Genetics Program, Charles Perou uses genomics to characterize the diversity of breast cancer tumors — research that helps doctors guarantee patients more individualized care. In 2011, he cofounded GeneCentric, which uses personalized molecular diagnostic assays and targeted drug development to treat cancer.
In 2015, geneticist Aravind Asokan started StrideBio with University of Florida biochemist Mavis Agbandje-McKenna. The gene therapy company develops novel adeno-associated viral (AAV) vector technologies for treating rare diseases. Although still in its infancy, the company has already partnered with CRISPR Therapeutics and received an initial investment from Hatteras Venture Partners. Asokan has spent nearly a decade studying AAV — and even helped to, previously, cofound Bamboo Therapeutics, acquired by Pfizer for $645 million just last year.
In 2016, current genetics department Chair Fernando Pardo-Manuel de Villena challenged both Darwin’s theory of natural selection and Mendel’s law of segregation through researching a mouse gene called R2d2. In doing so, he found that a selfish gene can become fixed in a population of organisms while, at the same time, being detrimental to “reproductive fitness” — a discovery that shows the swiftness at which the genome can change, creating implications for an array of fields from basic biology to agriculture and human health.
A former student of Oliver Smithies, Beverly Koller uses gene targeting in mice to better understand diseases like cystic fibrosis, asthma, and arthritis — research that will ultimately lead to better treatments. Similarly, Mark Heise observes mice to study diseases caused by viruses including infectious arthritis and encephalitis (inflammation of the brain). Both researchers are part of the Collaborative Cross project, a large panel of inbred mouse strains that help map genetic traits — a resource that is UNC lead, according to Magnuson.
Genetics research stems far beyond the UNC School of Medicine. In 2009, for example, chemist Kevin Weeks and his research team decoded the HIV genome, advancing the development of new therapies and treatments. UNC sociologist Gail Henderson runs the Center for Genomics and Society, which provides research and training on ethical, legal, and social implications of genomic research. In 2015, UNC Eshelman School of Pharmacy Dean Bob Blouin helped the school become the first U.S. hub to join the international Structural Genomics Consortium — focused on discovering selective, small molecules and protein kinases to help speed the creation of new medicines for patients.
From crutches to a 5K
After just three months of treatment, Davis walked fully unsupported for the first time since she was 6 years old. She’s since traversed Hershey Park in Pennsylvania, strolled around the World Trade Center in New York, and regularly participated in yoga and spin classes. This past May, she walked her first 5K. “I have crazy endurance,” she says. “When your body feels good, you just want to keep on going.”
Perhaps, more importantly, Davis is able attend Alex’s sports games without assistance. “When I used to walk into the gym on crutches to watch my oldest son play basketball, everyone would look at my crutches and my legs,” she says. “Now, when I go watch my youngest son play, I have so much more confidence walking in to the gym. People see me.”
Carolina’s vibrant people and programs attest to the University’s long-standing place among leaders in higher education since it was chartered in 1789 and opened its doors for students in 1795 as the nation’s first public university. Situated in the beautiful college town of Chapel Hill, N.C., UNC has earned a reputation as one of the best universities in the world. Carolina prides itself on a strong, diverse student body, academic opportunities not found anywhere else, and a value unmatched by any public university in the nation.
After undergoing batteries of tests without a conclusive diagnosis, Calvin Lapidus underwent exome sequencing at UCLA, which enabled doctors to identify his rare condition, known as Pitt-Hopkins syndrome.
When Audrey Lapidus’ 10-month old son, Calvin, didn’t reach normal milestones like rolling over or crawling, she knew something was wrong.
“He was certainly different from our first child,” said Lapidus, of Los Angeles. “He had a lot of gastrointestinal issues and we were taking him to the doctor quite a bit.”
Four specialists saw Calvin and batteries of tests proved inconclusive. Still, Lapidus persisted.
“I was pushing for even more testing, and our geneticist at UCLA said, ‘If you can wait one more month, we’re going to be launching a brand new test called exome sequencing,’” she said. “We were lucky to be in the right place at the right time and get the information we did.”
In 2012, Calvin Lapidus became the first patient to undergo exome sequencing at UCLA. He was subsequently diagnosed with a rare genetic condition known as Pitt-Hopkins syndrome, which is most commonly characterized by developmental delays, possible breathing problems, seizures and gastrointestinal problems.
Though there is no cure for Pitt-Hopkins, finally having a diagnosis allowed Calvin to begin therapy. “The diagnosis gave us a point to move forward from, rather than just existing in that scary no-man’s land where we knew nothing,” Lapidus said.
“Unfortunately, there are a lot of people living in that no-man’s land, desperate for any type of answers to their medical conditions,” said Dr. Stanley Nelson, professor of human genetics and pathology and laboratory medicine at the David Geffen School of Medicine at UCLA. “Many families suffer for years without so much as a name for their condition.”
What exome sequencing allows doctors to do is to analyze more than 20,000 genes at once, with one simple blood test.
In the past, genetic testing was done one gene at a time, which is time-consuming and expensive.
“Rather than testing one sequential gene after another, exome sequencing saves time, money and effort,” said Dr. Julian Martinez-Agosto, a pediatrician and researcher at the Resnick Neuropsychiatric Hospital at UCLA.
The exome consists of all the genome’s “exons,” which are the coding portion of genes. Clinical exome sequencing is a test for identifying disease-causing DNA variants within the 1 percent of the genome which codes for proteins, the exons, or flanks the regions which code for proteins.
To date, mutations in the protein-coding parts of genes accounts for nearly 85 percent of all mutations known to cause genetic diseases, so surveying just this portion of the genome is an efficient and powerful diagnostic tool. Exome sequencing can help detect rare disorders like spinocerebellar ataxia, which progressively diminishes a person’s movements, and suggest the likelihood of more common conditions like autism spectrum disorder and epilepsy.
More than 4,000 adults and children have undergone exome testing at UCLA since 2012. Of difficult to solve cases, more than 30 percent are solved through this process, which is a dramatic improvement over prior technologies. Thus, Nelson and his team support wider use of genome-sequencing techniques and better insurance coverage, which would further benefit patients and resolve diagnostically difficult cases at much younger ages.
Since her son’s diagnosis, Lapidus helped found the Pitt-Hopkins Syndrome Research Foundation. “Having Calvin’s diagnosis gave us a roadmap of where to start, where to go and what’s realistic as far as therapies and treatments,” she said. “None of that would have been possible without that test.”
Next, experts at UCLA are testing the relative merits of broader whole genome sequencing to analyze all 6 billion bases that make up a person’s genome. The team is exploring integration of this DNA sequencing with state-of-the-art RNA or gene expression analysis to improve the diagnostic rate.
The entire human genome was first sequenced in 1990 at a cost of $2.7 billion. Today, doctors can perform the same test at a tiny fraction of that cost, and believe that sequencing whole genomes of individuals could vastly improve disease diagnoses and medical care.
For nearly 100 years, UCLA has been a pioneer, persevering through impossibility, turning the futile into the attainable.
We doubt the critics, reject the status quo and see opportunity in dissatisfaction. Our campus, faculty and students are driven by optimism. It is not naïve; it is essential. And it has fueled every accomplishment, allowing us to redefine what’s possible, time after time.
This can-do perspective has brought us 12 Nobel Prizes, 12 Rhodes Scholarships, more NCAA titles than any university and more Olympic medals than most nations. Our faculty and alumni helped create the Internet and pioneered reverse osmosis. And more than 100 companies have been created based on technology developed at UCLA.
Following centuries of curiosity and uncertainty about the human brain, a recent neuroimaging study [Nature Protocols] will provide us with a way to study the live human brain non-invasively. Prior to the advent of neuroimaging, neuroscientists relied solely on post-mortem, or after death, autopsies to gain insight into the workings of the brain. By contrast, neuroimaging employs a variety of techniques to structurally or functionally image the brain without surgical intervention. A multidisciplinary team of Yale researchers has developed connectome-based predictive modeling (CPM), a computational model capable of predicting human behavior based on how one’s brain is wired.
Some commonly used brain imaging techniques include computed tomography (CT) scanning, function magnetic resonance imaging (fMRI), and electroencephalography (EEG). fMRI measures brain activity by detecting changes in oxygenated blood flow through specific areas of the brain. Specifically, the ability to detect these changes by fMRI takes advantage of the difference in the magnetic properties of oxygenated and deoxygenated blood. CPM uses fMRI to observe activity in specific regions of the brain and subsequently derive brain connectivity data for use in predicting an individual’s behavior.
The human connectome is a network of neural connections between different regions of the brain. These connections can be determined by identifying regions with simultaneous activity in the brain. The model developed by Yale researchers can characterize these neural connections more comprehensively by utilizing a connectivity matrix acquired from fMRI data. In a nutshell, each row in this matrix represents one of 300 regions of interest in the brain, and the data within each row describe the functional relationships between this region and the remaining 299 regions. Since humans have unique brain connectivity, and thus unique connectivity matrices, your brain’s functional connectivity can be used to predict various aspects of your behavior. CPM provides a way to extract that information and interpret it in meaningful ways.
The predictive model is constructed by gathering connectivity matrices from many people, and is then used to predict behavioral traits of a new person based on their connectivity matrix. The predictive power of CPM has immense clinical significance. Matrix data can be used to predict and analyze whether an individual has paranoia, delusions, schizophrenic symptoms, and other conditions. Additionally, psychiatric disorders could be more effectively diagnosed with the help of CPM. The current diagnostic protocol for such disorders, the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), has been met with mixed results since categorization of patients is based solely on identifiable symptoms. Implementing CPM for diagnostic purposes could allow for more thorough and scientific categorization that could ultimately improve the quality of mental health care.
Although CPM has not yet reached the stage of clinical application, future directions for this research are boundless. According to Professor Todd Constable, senior author of the study, one such direction could include identifying circuits that function aberrantly in certain diseases. Mechanistically understanding these diseases would in turn contribute to the development of more personalized and targeted treatments. “CPM has already been demonstrated to predict one’s fluid intelligence and attentive performance,” said Constable, who believes that many other traits can be similarly predicted. Another question that has yet to be answered is how the brain’s connectivity changes over time with aging and development. In contrast to DNA, our genetic code which is relatively static in comparison, brain connectivity is much more dynamic. This dynamism further challenges our efforts to study the brain.
The novelty of CPM lies in the fact that it is the first whole-brain connectome study of its kind. Up until recently, a major limitation for connectivity research had been an inadequate amount of individual connectome data from which to develop models for predicting complex behaviors. While previously only local brain connectivity could be studied given the amount of data available, the launch of the Human Connectome Project (HCP) in 2009 has supplied a mass of connectome data that allows whole-brain connectivity studies to be done for the first time. HCP is a large-scale effort to collect and share human connectome data in order to address fundamental questions about the functional connectivity of the human brain. To further this goal, the Yale researchers have published an algorithm for implementing CPM to build predictive models. This provides researchers around the world with the tools to contribute to the ongoing study of the human brain using predictive modeling.
Yale University comprises three major academic components: Yale College (the undergraduate program), the Graduate School of Arts and Sciences, and the professional schools. In addition, Yale encompasses a wide array of centers and programs, libraries, museums, and administrative support offices. Approximately 11,250 students attend Yale.
Pulmonary medicine physician Maha Farhat and mathematician and evolutionary biologist Michael Baym join forces in the Department of Biomedical Informatics to stem the rising tide of drug resistance. Image: HMS. Rick Groleau.
A mathematician and a pulmonologist walk into a bar…
As tales of unlikely convergences go, this one is about the improbable intersection of big data and clinical efforts to combat bacterial drug resistance. Except in this case, the paths of mathematician Michael Baym and pulmonologist Maha Farhat crossed in the Department of Biomedical Informatics at Harvard Medical School.
Farhat and Baym are the newest faculty members of a young but rapidly growing department aspiring to improve diagnoses and catalyze treatments by translating information into practical clinical knowledge.
Farhat and Baym are on a quest to do just that.
“We met very recently and, as it turns out, we have a lot of common threads in our work,” Farhat said.
For one, they share a passion for unraveling the evolutionary mysteries of microbial drug resistance and curbing its spread. They also each harbor a belief that the most promising pathway to solving drug resistance lies in using large-scale genomic data and computation.
“We ended up basically identifying the same problem taking a very similar angle on a solution, despite coming from completely different backgrounds and skill sets,” Baym said.
The TB warrior
As an idealistic first-year medical student at Montreal’s McGill University, Farhat set out to find her professional raison d’être among the diseases that cause the greatest morbidity and mortality.
“I was shocked to find out that TB was still one of the top five causes of death and the number one infectious disease killer globally,” Farhat said.
One of Farhat’s formative experiences was her collaboration with pulmonologist Dick Menzies, of the Montreal Chest Institute. He spent his mornings researching diagnostic tests for TB and his afternoons taking care of patients and doing procedures.
Smitten by such intellectual dexterity, Farhat decided she too wanted to pursue life as a physician-scientist. Farhat helped Menzies design a clinical calculator to help physicians interpret results of the tuberculin skin test—the most commonly used screen for exposure to TB. The test requires injecting a small amount of TB protein in a person’s forearm and observing the skin reaction to determine past exposure to the germ. This test, however, is by itself a notoriously unreliable predictor of actual infection.
The TB calculator that Menzies and Farhat developed used an algorithm that, in addition to factoring in the size of the skin welt, also included a range of patient characteristics to drive a more accurate interpretation. This experience was Farhat’s first encounter with the notion that computation could aid the design of clinical tools.
“It really got me interested in how one could take information and data and collate them in a user-friendly format to maximize their clinical use,” Farhat says.
These days, Fahrat uses decidedly more sophisticated methods. She is working to define the diversity of the TB genome as a way to understand genetic differences across TB strains and how such differences predict variations in response to treatment. Even so, her current work is very much philosophically aligned with her earlier experiences as a student.
“The premise is the same as the work we did with the TB calculator—developing the right methods, but, perhaps more importantly, putting them in a context that clinicians can use easily,” Farhat says. “This is where I see myself.”
Individualized medicine meets computation
Very quickly, Baym realized, that in order to harness evolution in any practical way, scientists had to define the genetic characteristics of an organism not merely on the level of the species but within the individual organism. In the context of bacterial infections, this means genetically analyzing strains in individual patients and tracking how the bacterium evolves to survive drug therapies.
Scaled-up, the approach could lead to valuable insights about the ways in which bacteria mutate to adapt to the combined pressures of drugs and the immune system.
In TB, such scaling up would first require cataloguing hundreds of thousands of TB genomes—a point the scientific community is rapidly approaching, Farhat said.
“We expect that in the next few years, we’ll have more than 100,000 different TB genomes sequenced,” Farhat said. “Currently, there are about 20,000 TB genomes in the public domain.”
Insights gleaned from such an array of data could lead to the development of therapies that avert or interrupt microbial mutations.
Such level of analysis could also help scientists profile and predict the behavior of a bacterial strain beyond its ability to mutate and survive drugs. For example, the data could yield clues about virulence or infectivity, such as whether a particular strain of TB is more likely to cause infection of the brain—TB meningitis—or the more commonly seen infection of the lungs.
Large-scale genomic data could also spark the design of point-of-care tests that detect the precise genetic subtype, including resistance-fueling mutations, within mere hours. By contrast, the current approach takes up to two months and involves collecting sputum from a patient, sending it to a lab and performing an antibiotic screen to determine which medication the bacterium responds to.
This means that for up to two months, patients are treated with drugs based on an imperfect guesstimate of their likelihood of carrying a resistant strain rather than actual evidence.
“This cuts to the core of the problem,” Baym said. “Clinicians don’t have access to enough data fast enough to make proper decisions about treatments.”
One of Farhat’s formative experiences was her collaboration with pulmonologist Dick Menzies, of the Montreal Chest Institute. He spent his mornings researching diagnostic tests for TB and his afternoons taking care of patients and doing procedures.
Smitten by such intellectual dexterity, Farhat decided she too wanted to pursue life as a physician-scientist. Farhat helped Menzies design a clinical calculator to help physicians interpret results of the tuberculin skin test—the most commonly used screen for exposure to TB. The test requires injecting a small amount of TB protein in a person’s forearm and observing the skin reaction to determine past exposure to the germ. This test, however, is by itself a notoriously unreliable predictor of actual infection.
The TB calculator that Menzies and Farhat developed used an algorithm that, in addition to factoring in the size of the skin welt, also included a range of patient characteristics to drive a more accurate interpretation. This experience was Farhat’s first encounter with the notion that computation could aid the design of clinical tools.
“It really got me interested in how one could take information and data and collate them in a user-friendly format to maximize their clinical use,” Farhat says.
These days, Fahrat uses decidedly more sophisticated methods. She is working to define the diversity of the TB genome as a way to understand genetic differences across TB strains and how such differences predict variations in response to treatment. Even so, her current work is very much philosophically aligned with her earlier experiences as a student.
“The premise is the same as the work we did with the TB calculator—developing the right methods, but, perhaps more importantly, putting them in a context that clinicians can use easily,” Farhat says. “This is where I see myself.”
The recovering mathematician
Baym has been always fascinated by evolution’s elegant simplicity—a set of basic rules and patterns creating life’s astounding complexity over a period of time.
While working on his doctorate in computational biology at MIT, he attended a talk on antibiotic resistance. It was a eureka moment for him. Drug resistance, Baym realized, was at its core an evolutionary phenomenon—bacteria adapting to and surviving an environmental challenge.
“I realized that a very basic understanding of evolution could really make a difference in how we tackle antibiotic resistance, and at the same time it was a very basic problem to test our understanding of evolution against.”
Baym started to talk to evolutionary biologists everywhere. During these conversations, one name kept popping up: Roy Kishony, then a professor of systems biology at Harvard Medical School. His work involved experiments in evolutionary manipulation. Baym cold-called Kishony. One thing led to another and Baym ended up as a post-doc in Kishony’s lab.
Individualized medicine meets computation
Very quickly, Baym realized, that in order to harness evolution in any practical way, scientists had to define the genetic characteristics of an organism not merely on the level of the species but within the individual organism. In the context of bacterial infections, this means genetically analyzing strains in individual patients and tracking how the bacterium evolves to survive drug therapies.
Scaled-up, the approach could lead to valuable insights about the ways in which bacteria mutate to adapt to the combined pressures of drugs and the immune system.
In TB, such scaling up would first require cataloguing hundreds of thousands of TB genomes—a point the scientific community is rapidly approaching, Farhat said.
“We expect that in the next few years, we’ll have more than 100,000 different TB genomes sequenced,” Farhat said. “Currently, there are about 20,000 TB genomes in the public domain.”
Insights gleaned from such an array of data could lead to the development of therapies that avert or interrupt microbial mutations.
Such level of analysis could also help scientists profile and predict the behavior of a bacterial strain beyond its ability to mutate and survive drugs. For example, the data could yield clues about virulence or infectivity, such as whether a particular strain of TB is more likely to cause infection of the brain—TB meningitis—or the more commonly seen infection of the lungs.
Large-scale genomic data could also spark the design of point-of-care tests that detect the precise genetic subtype, including resistance-fueling mutations, within mere hours. By contrast, the current approach takes up to two months and involves collecting sputum from a patient, sending it to a lab and performing an antibiotic screen to determine which medication the bacterium responds to.
This means that for up to two months, patients are treated with drugs based on an imperfect guesstimate of their likelihood of carrying a resistant strain rather than actual evidence.
“This cuts to the core of the problem,” Baym said. “Clinicians don’t have access to enough data fast enough to make proper decisions about treatments.”
A newly developed molecular TB test—now gaining wider use—can detect resistance within a few hours to the drug rifampin—a first-line therapy. Rifampin, however, is only one of an arsenal of TB drugs that clinicians use routinely.
Developing new and more exquisitely sensitive point-of-care TB tests demands the sampling of hundreds of thousands of patients with a given infection to define the circulating strains. The strains then would have to be analyzed genetically so that the tests can be calibrated to detect a wide range of mutations.
Point-of-care testing could be particularly transformative for TB care outside the United States, where the greatest disease burden is. In the United States, all patients diagnosed with TB are automatically tested for resistant forms of the infection. Elsewhere, the vast majority of patients are given the standard treatment, and resistance testing is only performed if a patient shows poor response to the drug therapy after two months of treatment.
But having large amounts of genomic data won’t, by itself, be enough to solve the problem, Farhat said.
“In order for us to be able to make the leap to using whole genome sequencing in point-of-care diagnostics we really have to understand the basic biology of each organism and the genetic markers of resistance.”
Driving evolution to a breaking point
When it comes to mutation and survival, every organism adapts and mutates up until it reaches a breaking point. That breaking point varies from organism to organism but generally results from a several pressures, such as drugs or the immune system, beyond which the organism can no longer adapt. Figuring out the breaking point for each bacterial strain and devising therapies that deliver that lethal punch would be the holy grail on the quest to curb microbial resistance.
In the case of TB, this may mean devising precision-targeted therapies or a combination of therapies that disarm the specific mutation that enables survival.
“You can treat an infection with a certain combination of therapies that will either work or fail in one of a handful of ways. If we can understand and predict these in advance, we can respond accordingly,” Baym said. “That’s the broad idea.”
This approach would precipitate a shift away from broad-spectrum treatments that target all possible mutations and strains toward ultra-narrow spectrum drugs that precision-target specific mutants within the pool of bacterial cells affecting individual patients.
“That’s the frontier we’re chasing,” Baym said.
The difference between where the standard of treatment is now and where Farhat and Baym aim to get would be akin to the recent shift in cancer care: away from carpet-bombing therapies to using a tumor’s genomic profile to individualize treatment.
“We would no longer just classify infectious diseases as TB or E.coli but subtype to the level of particular mutations within each person,” Farhat said.
Upping the price of a microbe’s survival
For germs, resistance doesn’t come cheap. The process of adapting to a pressure alters the microbe’s cellular machinery. It taxes it. Even though the changes allow the pathogen to become resistant, they harm the cellular apparatus in different ways. This, Farhat said, is the “fitness cost” an organism pays for its survival. As a result, the mutant cell starts to grow more slowly. Over time, as the cell tries to outcompete others, it will eventually accumulate a second set of mutations that compensate for the loss of cellular fitness. This second set of mutations—so-called compensatory mutations—could represent another therapeutic target.
Drugs that allow scientists to halt compensatory mutations could eradicate mutant strains before they proliferate and cause serious disease. Another option would be devising treatments that target the weakened mutant before it even acquires a compensatory mutation.
“Once you open the door to respond predictively to evolution, there’s a whole range of treatment strategies,” Baym said. “There’s a large but not infinite way to get resistance. We know we need more data than we have right now but we think that if we collect enough, we can define all of the ways that bacteria use to become resistant.”
Established in 1782, Harvard Medical School began with a handful of students and a faculty of three. The first classes were held in Harvard Hall in Cambridge, long before the school’s iconic quadrangle was built in Boston. With each passing decade, the school’s faculty and trainees amassed knowledge and influence, shaping medicine in the United States and beyond. Some community members—and their accomplishments—have assumed the status of legend. We invite you to access the following resources to explore Harvard Medical School’s rich history.
Harvard is the oldest institution of higher education in the United States, established in 1636 by vote of the Great and General Court of the Massachusetts Bay Colony. It was named after the College’s first benefactor, the young minister John Harvard of Charlestown, who upon his death in 1638 left his library and half his estate to the institution. A statue of John Harvard stands today in front of University Hall in Harvard Yard, and is perhaps the University’s best known landmark.
Harvard University has 12 degree-granting Schools in addition to the Radcliffe Institute for Advanced Study. The University has grown from nine students with a single master to an enrollment of more than 20,000 degree candidates including undergraduate, graduate, and professional students. There are more than 360,000 living alumni in the U.S. and over 190 other countries.
CRISPR-Cas3 is a subtype of the CRISPR-Cas system, a widely adopted molecular tool for precision gene editing in biomedical research. Aspects of its mechanism of action, however, particularly how it searches for its DNA targets, were unclear, and concerns about unintended off-target effects have raised questions about the safety of CRISPR-Cas for treating human diseases.
Harvard Medical School and Cornell University scientists have now generated near-atomic resolution snapshots of CRISPR that reveal key steps in its mechanism of action. The findings, published in Cell on June 29, provide the structural data necessary for efforts to improve the efficiency and accuracy of CRISPR for biomedical applications.
Through cryo-electron microscopy, the researchers describe for the first time the exact chain of events as the CRISPR complex loads target DNA and prepares it for cutting by the Cas3 enzyme. These structures reveal a process with multiple layers of error detection—a molecular redundancy that prevents unintended genomic damage, the researchers say.
High-resolution details of these structures shed light on ways to ensure accuracy and avert off-target effects when using CRISPR for gene editing.
“To solve problems of specificity, we need to understand every step of CRISPR complex formation,” said Maofu Liao, assistant professor of cell biology at Harvard Medical School and co-senior author of the study. “Our study now shows the precise mechanism for how invading DNA is captured by CRISPR, from initial recognition of target DNA and through a process of conformational changes that make DNA accessible for final cleavage by Cas3.”
Target search
Discovered less than a decade ago, CRISPR-Cas is an adaptive defense mechanism that bacteria use to fend off viral invaders. This process involves bacteria capturing snippets of viral DNA, which are then integrated into its genome and which produce short RNA sequences known as crRNA (CRISPR RNA). These crRNA snippets are used to spot “enemy” presence.
Acting like a barcode, crRNA is loaded onto members of the CRISPR family of enzymes, which perform the function of sentries that roam the bacteria and monitor for foreign code. If these riboprotein complexes encounter genetic material that matches its crRNA, they chop up that DNA to render it harmless. CRISPR-Cas subtypes, notably Cas9, can be programmed with synthetic RNA in order to cut genomes at precise locations, allowing researchers to edit genes with unprecedented ease.
To better understand how CRISPR-Cas functions, Liao partnered with Ailong Ke of Cornell University. Their teams focused on type 1 CRISPR, the most common subtype in bacteria, which utilizes a riboprotein complex known as CRISPR Cascade for DNA capture and the enzyme Cas3 for cutting foreign DNA.
Through a combination of biochemical techniques and cryo-electron microscopy, they reconstituted stable Cascade in different functional states, and further generated snapshots of Cascade as it captured and processed DNA at a resolution of up to 3.3 angstroms—or roughly three times the diameter of a carbon atom.
A sample cryo-electron microscope image of CRISPR molecules(left). The research team combined hundreds of thousands of particles into 2D averages (right), before turning them into 3D projections. Image: Xiao et al.
Seeing is believing
In CRISPR-Cas3, crRNA is loaded onto CRISPR Cascade, which searches for a very short DNA sequence known as PAM that indicates the presence of foreign viral DNA.
Liao, Ke and their colleagues discovered that as Cascade detects PAM, it bends DNA at a sharp angle, forcing a small portion of the DNA to unwind. This allows an 11-nucleotide stretch of crRNA to bind with one strand of target DNA, forming a “seed bubble.”
The seed bubble acts as a fail-safe mechanism to check whether the target DNA matches the crRNA. If they match correctly, the bubble is enlarged and the remainder of the crRNA binds with its corresponding target DNA, forming what is known as an “R-loop” structure.
Once the R-loop is completely formed, the CRISPR Cascade complex undergoes a conformational change that locks the DNA into place. It also creates a bulge in the second, non-target strand of DNA, which is run through a separate location on the Cascade complex.
Only when a full R-loop state is formed does the Cas3 enzyme bind and cut the DNA at the bulge created in the non-target DNA strand.
The findings reveal an elaborate redundancy to ensure precision and avoid mistakenly chopping up the bacteria’s own DNA.
CRISPR forms a “seed bubble” state, which acts as an initial fail-safe mechanism to ensure that CRISPR RNA matches its target DNA. Image: Liao Lab/HMS.
“To apply CRISPR in human medicine, we must be sure the system is accurate and that it does not target the wrong genes,” said Ke, who is co-senior author of the study. “Our argument is that the CRISPR-Cas3 subtype has evolved to be a precise system that carries the potential to be a more accurate system to use for gene editing. If there is mistargeting, we know how to manipulate the system because we know the steps involved and where we might need to intervene.”
Setting the sights
Structures of CRISPR Cascade without target DNA and in its post-R-loop conformational states have been described, but this study is the first to reveal the full sequence of events from seed bubble formation to R-loop formation at high resolution.
In contrast to the scalpel-like Cas9, CRISPR-Cas3 acts like a shredder that chews DNA up beyond repair. While CRISPR-Cas3 has, thus far, limited utility for precision gene editing, it is being developed as a tool to combat antibiotic-resistant strains of bacteria. A better understanding of its mechanisms may broaden the range of potential applications for CRISPR-Cas3.
In addition, all CRISPR-Cas subtypes utilize some version of an R-loop formation to detect and prepare target DNA for cleavage. The improved structural understanding of this process can now enable researchers to work toward modifying multiple types of CRISPR-Cas systems to improve their accuracy and reduce the chance of off-target effects in biomedical applications.
“Scientists hypothesized that these states existed but they were lacking the visual proof of their existence,” said co-first author Min Luo, postdoctoral fellow in the Liao lab at HMS. “The main obstacles came from stable biochemical reconstitution of these states and high-resolution structural visualization. Now, seeing really is believing.”
“We’ve found that these steps must occur in a precise order,” Luo said. “Evolutionarily, this mechanism is very stringent and has triple redundancy, to ensure that this complex degrades only invading DNA.”
Additional authors on the study include Yibei Xiao, Robert P. Hayes, Jonathan Kim, Sherwin Ng, and Fang Ding.
This work is supported by National Institutes of Health grants GM 118174 and GM102543.
Established in 1782, Harvard Medical School began with a handful of students and a faculty of three. The first classes were held in Harvard Hall in Cambridge, long before the school’s iconic quadrangle was built in Boston. With each passing decade, the school’s faculty and trainees amassed knowledge and influence, shaping medicine in the United States and beyond. Some community members—and their accomplishments—have assumed the status of legend. We invite you to access the following resources to explore Harvard Medical School’s rich history.
Harvard is the oldest institution of higher education in the United States, established in 1636 by vote of the Great and General Court of the Massachusetts Bay Colony. It was named after the College’s first benefactor, the young minister John Harvard of Charlestown, who upon his death in 1638 left his library and half his estate to the institution. A statue of John Harvard stands today in front of University Hall in Harvard Yard, and is perhaps the University’s best known landmark.
Harvard University has 12 degree-granting Schools in addition to the Radcliffe Institute for Advanced Study. The University has grown from nine students with a single master to an enrollment of more than 20,000 degree candidates including undergraduate, graduate, and professional students. There are more than 360,000 living alumni in the U.S. and over 190 other countries.
Oxford University’s Old Road Campus Research Building. Credit: OUImages / Rob Judges.
The challenge
“We started the first trial in 2002 and we finished the efficacy trial in 2013.”
Nine years of trials. That was on top of the time taken to develop the thing in the first place. That’s a long time.
Le Mans takes 24 hours. The Marathon des Sables, billed as the toughest footrace on earth, is over in six days. The Vendee Globe round the world yacht race can take 150 or so days. These are all considered defining tests of human endurance.
Vaccine development may not be as physically demanding, but to keep plugging away for twenty years surely requires mental resilience. For Le Mans, the MdS and the Vendee Globe, the finish line is known, fixed; for vaccines, new data may move the finish line at any time. Imagine getting halfway round the world to discover that not only has the end moved two hundred miles further away, but you’re heading in the wrong direction…
So I decided to ask three Oxford scientists with a wealth of vaccine knowledge about what they did and why they kept doing it.
What happens in a biomedical lab? Filmed in Oxford University’s Old Road Campus Research Building.
The first was Helen McShane, Professor of Vaccinology, specialist in TB, who began by outlining the vaccine development process.
Helen McShane, Professor of Vaccinology. Credit: John Cairns.
Professor Andrew Pollard, director of the Oxford Vaccine Group. No image credit.
Professor Adrian Hill, director of the Jenner Institute. Credit: John Cairns.
‘We design and construct vaccines. We then test them in different animal models. When they look good we then move them into early clinical testing. And when they look really good we then move them into testing through my collaborations in science in Africa.’
Put it like that and it sounds quite straightforward. Just along from Professor McShane is Professor Adrian Hill, director of Oxford’s dedicated vaccine research centre, the Jenner Institute. He colours in that outline, drawing on his own experience in malaria vaccine research.
‘From the idea to licensing a vaccine is a very long road. You can divide it into two very large parts. One is pre-clinical — before you start vaccinating people — and the second part is clinical, which is all the clinical trials you would do to go from your first human vaccinee to convincing a regulator that the vaccine was safe and effective. Each of those will take years.
‘In a way it’s easier to describe the clinical development because it happens in three phases. Phase one, which tends to be a safety trial to show that the vaccine doesn’t do any harm. You typically measure some immune responses. Then in phase two you try to get the dose optimised. You figure out how many immunisations you need to give, what the interval between them should be — the immunisation regime — and you test the vaccine in a lot more people and often in different settings. You might in malaria do that in the country of origin of the vaccine, in our case the UK, say in a West African population where there is Malaria, and then you’d go on from adults where you typically test a vaccine first to the group you really want to immunise, which in the case of malaria is young infants. That takes time, because you can’t just one day immunise a lot of adults and the next week immunise babies — you have to age deescalate carefully.
‘And all the time you’re monitoring safety because any serious adverse event that pops up at any stage of the clinical process can flag the end for that vaccine candidate. So that would typically take five or ten years of clinical development — if everything goes well.
‘Of course one of the challenges with public sector vaccine development, where you’re raising money to fund your next clinical trial all the time, is every time you’ve done a trial to persuade the next group of funders or next funding agency that the results are promising enough to justify going forward.
‘So there’s continuous review and unfortunately the amount of money required to keep going gets larger and larger. A phase one trial is typically maybe half a million pounds, a phase two trial is millions of pounds and a phase three trial is many tens of millions of pounds, so people have to be more and more confident at every stage that this is going to be a real product that will save lives.
‘On the pre-clinical side of things, it’s faster but it’s more complex. You have many more decisions to make in early stage research, for example — what antigen you will use in your malaria vaccine — there are thousands. What way you will deliver the antigen? That’s what we call immunogen design — how will you design the vaccine so that you get a strong immune response that will last for a long time? If it doesn’t last for a long time, your vaccine won’t work for very long.
‘Other questions are very relevant, for example are you going to be able to manufacture this vaccine, not just to do a trial but eventually to vaccinate maybe 100 million babies around the world every year to stop them getting malaria. That isn’t going to be possible for every type of vaccine you think of and for some that it’s possible for it will be too expensive, because we can’t sell a malaria vaccine for 100 dollars; it has to be cheaper than that because someone else is going to be paying. So there are lots of considerations, there’s lots of debate. You must test your vaccines in animals, for several reasons: to establish safety, to look at the immune response that’s produced to see if it works in small animals. If it doesn’t you’re probably not going to be supported to go further into human testing. So we have actually more people doing pre-clinical malaria research than we have doing malaria clinical trials.’
Given in such detail, it sounds daunting enough. Yet, Professor McShane adds another detail — a critical one. To trial a candidate vaccine requires volunteers, people willing literally to roll up their sleeves and be injected with a new biological agent, or in the case of the later stages of her MV85A TB vaccine study, willing to volunteer their baby.
‘The first study you do is what’s called a ‘phase one — first in man’ and that is literally the first time anything has been tested in man. Those are very small studies, typically 12–20 subjects. We then test it in other populations that are relevant for TB vaccines, so for example we would look at safety and immunogenicity in what we call latently infected people or people with HIV, who are more likely to get TB. Those trials would also take 12–20 subjects.
‘We would then move to phase 2a studies in the developing world where TB is prevalent. Here the numbers go up a bit so you then vaccinate 50 to 100 subjects. One of the important target populations for a TB vaccine is infants — because they get a lot of TB. If you give a vaccine to an infant the best case scenario is that you give it at the same time as all their other vaccines because then you minimise additional visits to the clinic and you’re more likely to vaccinate more children. To do that you have to make sure the new vaccine you’re adding doesn’t interfere with the existing vaccines, so you do what’s known as a non-interference study. We did one with 300 babies in the Gambia.
‘And then there’s a big jump between those studies and what we call the phase 2b efficacy trials and for those studies you need very big numbers because although there’s a lot of TB in the world, in any population the incidence — new cases per year — is actually quite low. So you need a high incidence population because you need as many new cases as possible — because that’s your measure of efficacy. you’re counting the number of new cases in a given time period in your vaccine arm versus your placebo arm. So in our efficacy trial we had 3000 babies.’
More common diseases might require fewer volunteers than Professor McShane’s 3000, but even then you’ll need hundreds of people to agree to take part. Without enough volunteers, you have no clinical trials; without clinical trials, you have no progress. Yet, not only are there volunteers, some of those in Oxford who take part in early trials choose to return again and again to support research.
A mile away is Professor Andrew Pollard, director of the Oxford Vaccine Group, which specialises in paediatric vaccines. He echoes the issue of volunteer recruitment.
‘In trials the delivery is an enormous undertaking because of the cost, the logistics and the regulation and just getting out there to get volunteers in to do very complex experiments with them.
‘What’s exciting about being at Oxford is we can do it and it works. There’s such a good machine and wonderful people you can press a button and do a study like VAST: We import a vaccine from India, give it to volunteers, challenge them a month later with a pathogen that in some parts of the world is killing people, and at the end of it have a readout that helps inform global policy. You can’t really beat that.’
The outcome
So that’s the practical challenge. But is it worth it? Does all that work finally pay off?
Not always.
The three researchers seem sanguine about it. Professor McShane wryly notes: ‘Inevitably ‘there are lots of ups and downs along the way.’
‘The first four volunteers we vaccinated with MV85A, we saw enormously strong responses to that vaccine, much more than we were expecting and I still remember the day my postdoc walked round the lab with the results and showed me them and I thought he must have made a mistake. They were twenty times higher than we were expecting the responses to be.’
Professor Pollard calmly tells me that the majority of vaccines in most fields that have been developed don’t even step into phase one, and many of those that do don’t progress much from there:
‘We don’t understand the immune system quite well enough to know why, when it doesn’t work, it doesn’t. The reality of day to day doing research is that there is lots of stuff that doesn’t work, which is a bit frustrating.
‘There is a huge challenge to get to phase I because of the costs of manufacturing a vaccine to the standards required by regulators…..but for those candidates that look promising further development is very much driven by the likely size of the market and the potential for large investment required to get to phase III being recouped.’
I push each of them on this — surely they feel more than slight frustration?
Professor Hill describes a negative result as ‘like losing a football game only worse because this football game has sometimes lasted two or three years — if not more. And you finally get it into the clinic, do an efficacy trial and there’s no efficacy.
‘I’ve sat in this chair and just started at a piece of paper which says that vaccine isn’t working at all and that’s a bad experience.’
Professor McShane describes her experience with MV85A. After the joy of those unexpectedly positive results, the vaccine progressed to that trial in 3000 babies:
‘Eight of us — the eight people who led the trial — pretty much locked ourselves in a hotel room in Cape Town and got the results. None of us had seen the results and we were literally handed a folder with all the results in at 9 o’clock on a Monday morning. And we all sat and looked at the results together and all looked at each other.
‘Five years of an efficacy trial and ten years of vaccine development, to discover that the vaccine, whilst safe, had not improved protection against TB compared to BCG alone. I was enormously disappointed; pleased it was safe, pleased that there was absolutely no evidence that we had done any harm with this vaccine, but clearly it hadn’t worked.’
Adrian Hill describes the first field trial of a vaccine his team did in West Africa in 2001. It was the first time they’d really tested their cellular immunity approach. It showed no significant efficacy.
However, he notes that the study revealed firstly that it was not going to be quick and easy and secondly that they were a long way from getting there and would need to do a lot of optimisation. It was, he realised, going be a long road. The first attempt at a malaria vaccine was produced in 1908 and that we still don’t have a vaccine for the disease.
Yet there are successes. Andrew Pollard points out that half of the vaccines in the UK immunisation schedule have trials from Oxford underpinning their development:
‘You look at the UK immunisations schedule and we’ve more than doubled the number of vaccines we give to children compared with the 90s, which is fantastic for public health. Look at the mortality data for children and they are less likely to die now than twenty years ago. There are probably many reasons for that but vaccines are part of it. There are measurable effects in the population; it’s much more dramatic in the developing world where there are huge reductions in the death rate but there is still a measurable fall in childhood mortality even in this country. I feel quite privileged to have been part of that process.’
The motivation
In all the discussions it is clear that the challenges are significant and the outcomes variable. So why?
With timescales of decades offering only uncertain success, where do they find the strength to keep going? Discover the vaccine for X and you can look back and say it was all worth it. But what keeps you going when it looks like you won’t get there?
The answers I get show that that understanding is too simple: It’s tempting but wrong to look at vaccine development in a binary way — you develop a vaccine and it either works or it doesn’t.
But none of the researchers take that view. Compare these three answers describing the response to trials that have not shown a vaccine to work:
Adrian Hill: ‘The motivation is firstly to understand why it didn’t work and secondly to realise that by it not working you have learned something that is usually pretty important.’
Andrew Pollard: ‘We’re learned something that means we don’t pursue that avenue in the future or we know how to do something that we didn’t know before — we’ve learnt some of the technologies that were needed.’
Helen McShane: ‘It’s my view that we will make progress in this field by iteratively doing trials, getting results, feeding them back, using those results to improve the animal models, improve the immunological markers that we use and improve the design of our next generation vaccines.’
Everything is an opportunity to learn and by learning as much as possible, whatever the headline outcome, it seems to me that researchers can mitigate the blow that comes from that outcome.
Helen McShane on fighting TB in South Africa.
Helen McShane’s story of that South African TB trial illustrates that. She described what happened after the initial — disappointing — result.
‘I guess we got to Monday afternoon and it took us a few hours to recover from the disappointment collectively as a group and then we realised that yes, this was disappointing but TB vaccines are a difficult field because we don’t have a correlate, we don’t know which — if any — of the animal models predict human efficacy — the only way we can test if a vaccine is going to work is to do these trials.
‘I think we were all and are all utterly committed to learning as much as we can from this study — and my lab has just finished conducting an enormous correlate analysis on the blood samples taken from all of those babies to try to find out more about the immune response we should try to induce — so that we can move on and design the next vaccine. You have to just carry on — TB remains a very important cause of death and disease throughout the world.
‘Even in that first week when we got that efficacy trial result I was starting to think well we could do this instead. That’s the joy of science really — that there are always other things to try. We will have five or six projects ongoing; the nature of science is that some of those will work and some those won’t work but as long as they don’t all bomb at once then there’s always something to keep you going. There’s always another idea, there’s always something you can do to make it better. I guess it’s just got me hooked.’
That excitement — the sense of enquiry, discovery and potential — is also clear when I speak to Andrew Pollard. He tells me how technology, such as gene sequencing, means that we can understand much more about both the pathogens and the immune response to them.
‘It’s almost that we’re getting to the top of a hill — we’re not quite sure what’s over the top of the hill in the way that we use technology to understand immune responses. We’re getting vast amount of data from genomes, transcriptomes and so on. It feels like we’re developing this enormous new multi-parameter dataset that will help us understand the immune system and how complex it is.
‘That’s exciting although our problem is processing that amount of data to turn it into something useful but it feels like when we get over that it is just going to the transform the way we use that information to design the next generation of vaccines that hopefully will be safer — we’ll know what gives you a sore arm or a fever and we’ll stop those things from happening — and perhaps one day we will also be able to design out risks for developing rare serious side effects. So if you can identify all those aspects and at the same time find what makes really good immune responses that protect you, future vaccines could be a single shot that protects you for life.’
Do not be fooled into thinking that this is the scientific excitement of academics divorced from reality. Professor McShane walks across the road from her office each week, to where Dr McShane runs an HIV clinic.
‘It’s very grounding because I go from this wonderful academic stimulating environment where every day I have fascinating conversations. I have this wonderful team of people and this wonderful team of collaborators that I have really interesting conversations with — so then I just go and get my feet put back on the ground and see real life at its rawest.’
When I ask Professor Pollard about highs and lows, I do so expecting him to talk about moments in research.
‘It’s the people stuff which is the best and the worst. The science is what gets you out of bed in the morning. The worst things are some of the personal tragedies that happen to the staff that you work with.
‘It’s not the science, which is par for the course — you know, your ups and downs: you get the excitement of the paper coming out or the discovery of something, your work being used to inform policy decisions. For me, it’s the student getting their DPhil and launching on their career or sometimes leaving Oxford and getting their first job after they’ve finished. So it’s the people things that are the bit that matter the most.’
It seems vaccine research has two drivers: Science and humanity. There’s no doubt that all three experienced researchers are still excited by the journey of discovery they are on. However, there’s also no doubt that they are motivated by the desire to do something good for people. In the end, it’s something Helen McShane said that sticks most in the mind, part of her answer when asked how she kept going.
The University
I ask Adrian Hill whether it takes a certain type of person to do vaccinology.
‘I think we are self-selected. Just to raise money is tough going — success rates are low. I think you can see the pathway by which something should work and feel you can make it work.’
That determination to make it work is how in the last sixteen years Oxford has become a key centre for vaccine research. In 1999, when Adrian Hill began trialling his first malaria vaccine Oxford had no other vaccine makers, although there was a small unit testing vaccines made by other people. However, Professor Hill was supported by long-time Oxford partner The Wellcome Trust.
In many ways that reflects a wider development. Despite it being 220 years since Edward Jenner’s first vaccination, vaccinology has only been seen as a research discipline in its own right in the last twenty to thirty years.
It used to be that companies made vaccines and some universities did trials. That model has changed, driven by the increasing complexity of vaccine development when faced with diseases like malaria and HIV. The intensive, prolonged programmes of research required are very unlikely to get approval from investors. As Adrian Hill puts it:
‘If we’re ever going to crack these tough vaccines like cancer, like HIV, like TB, you need a substantial effort in major research universities.’
At the same time, major funders like the Wellcome Trust and the Gates Foundation have focussed on global inequality and the paradox that science can put men on the moon yet not stop babies dying of common infectious diseases on earth. In the last fifteen years this large scale funding for global health has focussed on vaccination because of its cost effectiveness as a healthcare intervention.
This has led to a realisation that vaccinology is a form of translational research that you can carry out in a university from fundamental science through manufacturing into clinical development and even to late stage clinical trials. All of that can be done at Oxford, from the structural testing of possible antigens to clinical trials using the University’s network of overseas units.
In 2005, an agreement saw the Jenner Institute relocate to Oxford, with a statement of intent that it would be judged on its ability to develop and test new vaccine candidates. Meanwhile, the Oxford Vaccine Group has continued to develop its speciality in paediatric and maternal vaccines.
The University provides the core facilities that allow researchers to pursue vaccines for diseases from RSV to Cancer. They even include an in-house clinical manufacturing facility where batches of trial vaccines can be produced and where processes can be developed to ensure that an effective vaccine can be made in a way that will scale up to meet global demand.
It is not just physical facilities however. Oxford’s research governance and oversight of clinical trials ensures that clinical research is of a quality that protects patients, reassures regulators and delivers robust results.
Beyond these practicalities, the development has means that there is a critical mass of scientists who can exchange ideas and learn from each other. Little wonder that some of the best researchers wanting to get into the field want to do that at Oxford.
When they do, they will doubtless face similar situations to Professors Hill, McShane and Pollard — unexpectedly good and bad results, breakthroughs and apparent dead ends, days when progress seems swift and days when it seems reversed.
Their endurance events will build on those that have gone before and those going on now. They will learn from each other, draw support from each other and assist each other. Finish lines will move, sometimes closer, sometimes further away. New discoveries will offer more routes, new data will offer deeper understanding. They will keep going until — eventually — there will be vaccines for TB, for Malaria, for RSV and even for Cancer.
Oxford is a collegiate university, consisting of the central University and colleges. The central University is composed of academic departments and research centres, administrative departments, libraries and museums. The 38 colleges are self-governing and financially independent institutions, which are related to the central University in a federal system. There are also six permanent private halls, which were founded by different Christian denominations and which still retain their Christian character.
The different roles of the colleges and the University have evolved over time.
Moran Yassour, a postdoctoral researcher in the labs of Eric Lander and Ramnik Xavier at the Broad Institute, is a pioneer in one of biology’s hottest fields: the human microbiome. She’s researching how the circumstances of our birth and early life influence the origin and development of the microbes in our gut. Support from the BroadIgnite community has allowed her to investigate the differences in the gut bacteria between children born by C-section and those born vaginally. Here, she shares more about her research. The interview has been condensed and edited for clarity.
How did you come to study the infant microbiome? My mother is a computer science teacher, and I always loved genetics. When I was looking for undergrad programs, I came across a program that combined computer science and life science. I really enjoyed it and stayed in the same program for my master’s and Ph.D.
When I started my postdoc, I knew that I wanted to be in a field that’s a little bit more translational—something I could easily explain to my grandmother, or a stranger in the elevator, and they could understand what I’m doing and why it’s cool.
I started working on gut microbiome samples of adult patients with inflammatory bowel disease (IBD), but we also had a collaboration with a Finnish group with a cohort of children who got lots of antibiotics. I thought that was super interesting, because I had two young children at the time (a third is now on the way).
One day I was sitting in day care, and I realized that there are so many things that are different between them. Clearly, they’re going to share a lot of microbes because they’re all licking the same toys, but they have so many different eating habits. So it started me thinking about all the diversity that we see among children of the same age group, even among the same classroom in daycare.
What is the goal of your BroadIgnite project? In the Finnish data, we saw a pattern that was known before: kids born by C-section have a different microbe signature than kids born by vaginal delivery. What was really interesting and novel, though, was that 20 percent of kids born by vaginal delivery had the C-section microbial signature. We didn’t have the data to explain it. At some point, when I kept complaining that we don’t have all the things that could be relevant, I realized that we should just try to establish a new cohort that would have all the data we were missing.
Together with Dr. Caroline Mitchell (an OBGYN at MGH) we enrolled 190 families that came to deliver at MGH labor and delivery, and we collected samples from the kids and from different niches of the mother’s body. Now that most of the samples have been sequenced, we can get a better understanding of the differences in the microbial signatures. We can investigate questions like: do we see less transmission of bacterial strains from mother to child in C-section births? And can we identify the bacteria impacted the most?
What else might influence a baby’s microbiome? We have a project looking at breast milk versus infant formula. The third most common component in breast milk is a type of sugar called human milk oligosaccharides. There are 200 different types of these sugars, and each mother can have a different combination of these sugars in her milk. But the baby itself does not have the enzymes to break these down—basically the mother is feeding the baby’s gut bacteria.
In formula, none of these sugars are present, partly because they’re very expensive to make. But we also don’t know which sugars to add. We want to understand what the minimal and necessary set is that we can use to supplement formula that would best mimic breast milk. And so we’re trying to understand which bacteria could grow on which sugar, and which bacterial genes enable this potential growth for each sugar.
It also turns out that cow’s milk allergy is almost twice as prevalent in kids who are exclusively formula fed than in kids who are breastfed. Formula is based on cow’s milk, so it could just be that they get a lot of exposure to cow’s milk protein if they’re exclusively eating formula. On the other hand, we know that exclusively formula-fed babies have different gut bacteria. So that’s what we’re investigating with the Food Allergy Science Initiative, with a cohort of 180 kids, 90 of which got milk allergy and 90 of which did not.
What role did BroadIgnite play? Many young scientists lack confidence, so when other people think what you’re studying is important and that the methods you’re using are interesting, then that’s fun. The BroadIgnite funding was a really nice boost. It’s an honor to belong to such an extraordinary group of scientists.
Furthermore, I think that two strong advantages of the BroadIgnite funding are that I could get the funding started very fast, which helped me establish my new cohort, and that the preliminary results from these samples were instrumental in receiving a large NIH grant to further support my projects.
The Eli and Edythe L. Broad Institute of Harvard and MIT is founded on two core beliefs:
This generation has a historic opportunity and responsibility to transform medicine by using systematic approaches in the biological sciences to dramatically accelerate the understanding and treatment of disease.
To fulfill this mission, we need new kinds of research institutions, with a deeply collaborative spirit across disciplines and organizations, and having the capacity to tackle ambitious challenges.
The Broad Institute is essentially an “experiment” in a new way of doing science, empowering this generation of researchers to:
Act nimbly. Encouraging creativity often means moving quickly, and taking risks on new approaches and structures that often defy conventional wisdom.
Work boldly. Meeting the biomedical challenges of this generation requires the capacity to mount projects at any scale — from a single individual to teams of hundreds of scientists.
Share openly. Seizing scientific opportunities requires creating methods, tools and massive data sets — and making them available to the entire scientific community to rapidly accelerate biomedical advancement.
Reach globally. Biomedicine should address the medical challenges of the entire world, not just advanced economies, and include scientists in developing countries as equal partners whose knowledge and experience are critical to driving progress.
Rice University engineers have built a lab prototype of a flat microscope they are developing as part of DARPA’s Neural Engineering System Design project. The microscope will sit on the surface of the brain, where it will detect optical signals from neurons in the cortex. The goal is to provide an alternate path for sight and sound to be delivered directly to the brain. (Credit: Rice University)
Rice University engineers are building a flat microscope, called FlatScope [TM], and developing software that can decode and trigger neurons on the surface of the brain.
Their goal as part of a new government initiative is to provide an alternate path for sight and sound to be delivered directly to the brain.
The project is part of a $65 million effort announced this week by the federal Defense Advanced Research Projects Agency (DARPA) to develop a high-resolution neural interface. Among many long-term goals, the Neural Engineering System Design (NESD) program hopes to compensate for a person’s loss of vision or hearing by delivering digital information directly to parts of the brain that can process it.
Members of Rice’s Electrical and Computer Engineering Department will focus first on vision. They will receive $4 million over four years to develop an optical hardware and software interface. The optical interface will detect signals from modified neurons that generate light when they are active. The project is a collaboration with the Yale University-affiliated John B. Pierce Laboratory led by neuroscientist Vincent Pieribone.
Current probes that monitor and deliver signals to neurons — for instance, to treat Parkinson’s disease or epilepsy — are extremely limited, according to the Rice team. “State-of-the-art systems have only 16 electrodes, and that creates a real practical limit on how well we can capture and represent information from the brain,” Rice engineer Jacob Robinson said.
Robinson and Rice colleagues Richard Baraniuk, Ashok Veeraraghavan and Caleb Kemere are charged with developing a thin interface that can monitor and stimulate hundreds of thousands and perhaps millions of neurons in the cortex, the outermost layer of the brain.
“The inspiration comes from advances in semiconductor manufacturing,” Robinson said. “We’re able to create extremely dense processors with billions of elements on a chip for the phone in your pocket. So why not apply these advances to neural interfaces?”
Kemere said some teams participating in the multi-institution project are investigating devices with thousands of electrodes to address individual neurons. “We’re taking an all-optical approach where the microscope might be able to visualize a million neurons,” he said.
That requires neurons to be visible. Pieribone’s Pierce Lab is gathering expertise in bioluminescence — think fireflies and glowing jellyfish — with the goal of programming neurons with proteins that release a photon when triggered. “The idea of manipulating cells to create light when there’s an electrical impulse is not extremely far-fetched in the sense that we are already using fluorescence to measure electrical activity,” Robinson said.
The scope under development is a cousin to Rice’s FlatCam, developed by Baraniuk and Veeraraghavan to eliminate the need for bulky lenses in cameras. The new project would make FlatCam even flatter, small enough to sit between the skull and cortex without putting additional pressure on the brain, and with enough capacity to sense and deliver signals from perhaps millions of neurons to a computer.
Alongside the hardware, Rice is modifying FlatCam algorithms to handle data from the brain interface.
“The microscope we’re building captures three-dimensional images, so we’ll be able to see not only the surface but also to a certain depth below,” Veeraraghavan said. “At the moment we don’t know the limit, but we hope we can see 500 microns deep in tissue.”
“That should get us to the dense layers of cortex where we think most of the computations are actually happening, where the neurons connect to each other,” Kemere said.
A team at Columbia University is tackling another major challenge: The ability to wirelessly power and gather data from the interface.
In its announcement, DARPA described its goals for the implantable package. “Part of the fundamental research challenge will be developing a deep understanding of how the brain processes hearing, speech and vision simultaneously with individual neuron-level precision and at a scale sufficient to represent detailed imagery and sound,” according to the agency. “The selected teams will apply insights into those biological processes to the development of strategies for interpreting neuronal activity quickly and with minimal power and computational resources.”
“It’s amazing,” Kemere said. “Our team is working on three crazy challenges, and each one of them is pushing the boundaries. It’s really exciting. This particular DARPA project is fun because they didn’t just pick one science-fiction challenge: They decided to let it be DARPA-hard in multiple dimensions.”
Baraniuk is the Victor E. Cameron Professor of Electrical and Computer Engineering. Robinson, Veeraraghavan and Kemere are assistant professors of electrical and computer engineering.
In his 1912 inaugural address, Rice University president Edgar Odell Lovett set forth an ambitious vision for a great research university in Houston, Texas; one dedicated to excellence across the range of human endeavor. With this bold beginning in mind, and with Rice’s centennial approaching, it is time to ask again what we aspire to in a dynamic and shrinking world in which education and the production of knowledge will play an even greater role. What shall our vision be for Rice as we prepare for its second century, and how ought we to advance over the next decade?
This was the fundamental question posed in the Call to Conversation, a document released to the Rice community in summer 2005. The Call to Conversation asked us to reexamine many aspects of our enterprise, from our fundamental mission and aspirations to the manner in which we define and achieve excellence. It identified the pressures of a constantly changing and increasingly competitive landscape; it asked us to assess honestly Rice’s comparative strengths and weaknesses; and it called on us to define strategic priorities for the future, an effort that will be a focus of the next phase of this process.
For decades, HIV has successfully evaded all efforts to create an effective vaccine but researchers at The Scripps Research Institute (TSRI) and the La Jolla Institute for Allergy and Immunology (LJI) are steadily inching closer. Their latest study, published in a recent issue of Immunity, demonstrates that optimizing the mode and timing of vaccine delivery is crucial to inducing a protective immune response in a preclinical model.
More than any other factors, administering the vaccine candidate subcutaneously and increasing the time intervals between immunizations improved the efficacy of the experimental vaccine and reliably induced neutralizing antibodies. Neutralizing antibodies are a key component of an effective immune response. They latch onto and inactive invading viruses before they can gain a foothold in the body and have been notoriously difficult to generate for HIV.
“This study is an important staging point on the long journey toward an HIV vaccine,” says TSRI Professor Dennis R. Burton, Ph.D, who is also scientific director of the International AIDS Vaccine Initiative (IAVI) Neutralizing Antibody Center and of the National Institutes of Health’s Center for HIV/AIDS Vaccine Immunology and Immunogen Discovery (CHAVI-ID) at TSRI. “The vaccine candidates we worked with here are probably the most promising prototypes out there, and one will go into people in 2018,” says Burton.
“There had been a lot of big question marks and this study was designed to get as many answers as possible before we go into human clinical trials,” adds senior co-author Shane Crotty, Ph.D., a professor in LJI’s Division of Vaccine Discovery. “We are confident that our results will be predictive going forward.”
HIV has faded from the headlines, mainly because the development of antiretroviral drugs has turned AIDS into a chronic, manageable disease. Yet, only about half of the roughly 36.7 million people currently infected with HIV worldwide are able to get the medicines they need to control the virus. At the same time, the rate of new infections has remained stubbornly high, emphasizing the need for a preventive vaccine.
The latest findings are the culmination of years of collaborative and painstaking research by a dozen research teams centered around the development, improvement, and study of artificial protein trimers that faithfully mimic a protein spike found on the viral surface. At the core of this effort is the CHAVI-ID immunogen working group, comprised of TSRI’s own William R. Schief, Ph.D., Andrew B. Ward, Ph.D., Ian A. Wilson, D.Phil. and Richard T. Wyatt, Ph.D., in addition to Crotty and Burton. This group of laboratories in collaboration with Darrell J. Irvine, Ph.D., professor at MIT, and Rogier W. Sanders, Ph.D., professor at the University of Amsterdam, provided the cutting-edge immunogens tested in the study.
The recombinant trimers, or SOSIPs as they are called, were unreliable in earlier, smaller studies conducted in non-human primates. Non-human primates, and especially rhesus macaques, are considered the most appropriate pre-clinical model for HIV vaccine studies, because their immune system most closely resembles that of humans.
“The animals’ immune responses, although the right kind, weren’t very robust and a few didn’t respond at all,” explains Colin Havenar-Daughton, Ph.D., a scientific associate in the Crotty lab. “That caused significant concern that the immunogen wouldn’t consistently trigger an effective immune response in all individuals in a human clinical trial.”
In an effort to reliably induce a neutralizing antibody response, the collaborators tested multiple variations of the trimers and immunization protocols side-by-side to determine the best strategy going forward. Crotty and Burton and their colleagues teamed up with Professor Dan Barouch, M.D., Ph.D., Director of the Center for Virology and Vaccine Research at Beth Israel Deaconess Medical Center, who coordinated the immunizations.
The design of the study was largely guided by what the collaborators had learned in a previous study via fine needling sampling of the lymph nodes, where the scientists observed follicular helper T cells help direct the maturation steps of antibody-producing B cells. Administering the vaccine subcutaneously versus the more conventional intramuscular route, and spacing the injection at 8 weeks instead of the more common 4-6 weeks, reliably induced a strong functional immune response in all animals.
Using an osmotic pump to slowly release the vaccine over a period of two weeks resulted in the highest neutralizing antibody titers ever measured following SOSIP immunizations in non-human primates. While osmotic pumps are not a practical way to deliver vaccines, they illustrate an important point. “Depending on how we gave the vaccine, there was a bigger difference due to immunization route than we would have predicted,” says Matthias Pauthner, a graduate student in Burton’s lab and the study’s co-lead author. “We can help translate what we know now into the clinic.”
The Scripps Research Institute (TSRI), one of the world’s largest, private, non-profit research organizations, stands at the forefront of basic biomedical science, a vital segment of medical research that seeks to comprehend the most fundamental processes of life. Over the last decades, the institute has established a lengthy track record of major contributions to the betterment of health and the human condition.
The institute — which is located on campuses in La Jolla, California, and Jupiter, Florida — has become internationally recognized for its research into immunology, molecular and cellular biology, chemistry, neurosciences, autoimmune diseases, cardiovascular diseases, virology, and synthetic vaccine development. Particularly significant is the institute’s study of the basic structure and design of biological molecules; in this arena TSRI is among a handful of the world’s leading centers.
The institute’s educational programs are also first rate. TSRI’s Graduate Program is consistently ranked among the best in the nation in its fields of biology and chemistry.
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