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  • richardmitnick 12:52 pm on December 26, 2017 Permalink | Reply
    Tags: , , , J. William Schopf, John Valley, Mass spectrometry, , Oldest fossils ever found show life on Earth began before 3.5 billion years ago, SIMS-secondary ion mass spectrometer, Some represent now-extinct bacteria and microbes from a domain of life called Archaea, The study describes 11 microbial specimens from five separate taxa, ,   

    From U Wisconsin Madison and UCLA: “Oldest fossils ever found show life on Earth began before 3.5 billion years ago” 

    U Wisconsin

    University of Wisconsin

    UCLA bloc

    UCLA

    December 18, 2017
    Kelly April Tyrrell
    ktyrrell2@wisc.edu

    1
    Geoscience Professor John Valley, left, and research scientist Kouki Kitajima collaborate in the Wisconsin Secondary Ion Mass Spectrometer Lab (WiscSIMS) in Weeks Hall. Photo: Jeff Miller

    Researchers at UCLA and the University of Wisconsin–Madison have confirmed that microscopic fossils discovered in a nearly 3.5 billion-year-old piece of rock in Western Australia are the oldest fossils ever found and indeed the earliest direct evidence of life on Earth.

    2
    An epoxy mount containing a sliver of a nearly 3.5 billion-year-old rock from the Apex chert deposit in Western Australia is pictured at the Wisconsin Secondary Ion Mass Spectrometer Lab (WiscSIMS) in Weeks Hall. Photo: Jeff Miller

    The study, published Dec. 18, 2017 in the Proceedings of the National Academy of Sciences, was led by J. William Schopf, professor of paleobiology at UCLA, and John W. Valley, professor of geoscience at the University of Wisconsin–Madison. The research relied on new technology and scientific expertise developed by researchers in the UW–Madison WiscSIMS Laboratory.

    4
    J. William Schopf, U Wisconsin Madison

    5
    John Valley, UCLA

    2
    An example of one of the microfossils discovered in a sample of rock recovered from the Apex Chert. A new study used sophisticated chemical analysis to confirm the microscopic structures found in the rock are biological. Courtesy of J. William Schopf

    The study describes 11 microbial specimens from five separate taxa, linking their morphologies to chemical signatures that are characteristic of life. Some represent now-extinct bacteria and microbes from a domain of life called Archaea, while others are similar to microbial species still found today. The findings also suggest how each may have survived on an oxygen-free planet.

    The microfossils — so called because they are not evident to the naked eye — were first described in the journal Science in 1993 by Schopf and his team, which identified them based largely on the fossils’ unique, cylindrical and filamentous shapes. Schopf, director of UCLA’s Center for the Study of Evolution and the Origin of Life, published further supporting evidence of their biological identities in 2002.

    He collected the rock in which the fossils were found in 1982 from the Apex chert deposit of Western Australia, one of the few places on the planet where geological evidence of early Earth has been preserved, largely because it has not been subjected to geological processes that would have altered it, like burial and extreme heating due to plate-tectonic activity.

    But Schopf’s earlier interpretations have been disputed. Critics argued they are just odd minerals that only look like biological specimens. However, Valley says, the new findings put these doubts to rest; the microfossils are indeed biological.

    “I think it’s settled,” he says.

    Using a secondary ion mass spectrometer (SIMS) at UW–Madison called IMS 1280 — one of just a handful of such instruments in the world — Valley and his team, including department geoscientists Kouki Kitajima and Michael Spicuzza, were able to separate the carbon composing each fossil into its constituent isotopes and measure their ratios.

    Isotopes are different versions of the same chemical element that vary in their masses. Different organic substances — whether in rock, microbe or animal ­— contain characteristic ratios of their stable carbon isotopes.

    Using SIMS, Valley’s team was able to tease apart the carbon-12 from the carbon-13 within each fossil and measure the ratio of the two compared to a known carbon isotope standard and a fossil-less section of the rock in which they were found.

    “The differences in carbon isotope ratios correlate with their shapes,” Valley says. “If they’re not biological there is no reason for such a correlation. Their C-13-to-C-12 ratios are characteristic of biology and metabolic function.”

    Based on this information, the researchers were also able to assign identities and likely physiological behaviors to the fossils locked inside the rock, Valley says. The results show that “these are a primitive, but diverse group of organisms,” says Schopf.

    The team identified a complex group of microbes: phototrophic bacteria that would have relied on the sun to produce energy, Archaea that produced methane, and gammaproteobacteria that consumed methane, a gas believed to be an important constituent of Earth’s early atmosphere before oxygen was present.

    3
    UW–Madison geoscience researchers on a 2010 field trip to the Apex Chert, a rock formation in western Australia that is among the oldest and best-preserved rock deposits in the world. Courtesy of John Valley

    It took Valley’s team nearly 10 years to develop the processes to accurately analyze the microfossils — fossils this old and rare have never been subjected to SIMS analysis before. The study builds on earlier achievements at WiscSIMS to modify the SIMS instrument, to develop protocols for sample preparation and analysis, and to calibrate necessary standards to match as closely as possible the hydrocarbon content to the samples of interest.

    In preparation for SIMS analysis, the team needed to painstakingly grind the original sample down as slowly as possible to expose the delicate fossils themselves — all suspended at different levels within the rock and encased in a hard layer of quartz — without actually destroying them. Spicuzza describes making countless trips up and down the stairs in the department as geoscience technician Brian Hess ground and polished each microfossil in the sample, one micrometer at a time.

    Each microfossil is about 10 micrometers wide; eight of them could fit along the width of a human hair.

    Valley and Schopf are part of the Wisconsin Astrobiology Research Consortium, funded by the NASA Astrobiology Institute, which exists to study and understand the origins, the future and the nature of life on Earth and throughout the universe.

    Studies such as this one, Schopf says, indicate life could be common throughout the universe. But importantly, here on Earth, because several different types of microbes were shown to be already present by 3.5 billion years ago, it tells us that “life had to have begun substantially earlier — nobody knows how much earlier — and confirms it is not difficult for primitive life to form and to evolve into more advanced microorganisms,” says Schopf.

    Earlier studies by Valley and his team, dating to 2001, have shown that liquid water oceans existed on Earth as early as 4.3 billion years ago, more than 800 million years before the fossils of the present study would have been alive, and just 250 million years after the Earth formed.

    “We have no direct evidence that life existed 4.3 billion years ago but there is no reason why it couldn’t have,” says Valley. “This is something we all would like to find out.”

    UW–Madison has a legacy of pushing back the accepted dates of early life on Earth. In 1953, the late Stanley Tyler, a geologist at the university who passed away in 1963 at the age of 57, was the first person to discover microfossils in Precambrian rocks. This pushed the origins of life back more than a billion years, from 540 million to 1.8 billion years ago.

    “People are really interested in when life on Earth first emerged,” Valley says. “This study was 10 times more time-consuming and more difficult than I first imagined, but it came to fruition because of many dedicated people who have been excited about this since day one … I think a lot more microfossil analyses will be made on samples of Earth and possibly from other planetary bodies.”

    See the full U Wisconsin article here .
    See the full uCLA article by Stuart Wolpert here.
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    • stewarthoughblog 1:44 am on December 27, 2017 Permalink | Reply

      Schopf’s wishful speculation that what was discovered indicates life must be common is intellectually insulting with his failure that somehow live emerged rapidly, which strains the slow, methodical Darwinian theory of how life developed, given the relative complexity of the microorganisms. This is a wonderful discovery, but does nothing to solve the origin of life and raises serious questions about the power of naturalism to explain the origin of life as well as the rapid development of higher order complex organisms.

      The only extraterrestrial organisms that will be found will be those of Earth origin.

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  • richardmitnick 7:09 am on June 27, 2017 Permalink | Reply
    Tags: , , , , , , Data visualisation isn’t just for communication it’s also a research tool, Managing large data sets, Mass spectrometry, Minardo, , Sequencing, Visualising networks that change over time, VIZBI - an international visualisation community   

    From CSIRO: “Data visualisation isn’t just for communication, it’s also a research tool” 

    CSIRO bloc

    Commonwealth Scientific and Industrial Research Organisation

    27th June 2017
    Seán I. O’Donoghue
    James B. Procter

    1
    A collage of biological data visualisations. Image from C. Stolte, B.F. Baldi, S.I. O’Donoghue, C. Hammang, D.K.G. Ma, and G.T. Johnson, CC BY.

    At the heart of the scientific method lies the ability to make sense from data.

    However, this is a challenge in the fast-moving field of biotechnology, where new experimental methods are creating huge amounts of complex data. These data promise to revolutionise healthcare, food and agriculture, but it can be difficult to extract answers to specific research questions from these sets of numbers.

    Data visualisation can help. Our eyes deliver information very rapidly to our brains, and then sophisticated pattern recognition abilities take over. Well-designed visualisation tools can reveal discoveries that would otherwise remain buried.

    Below we highlight three data visualisation tools we have developed to help life scientists find relevant and useful information among the noise. The visualisation principles used in these tools are general and help in many complex data challenges.

    Managing large data sets

    Proteins and other molecules in our bodies exist as complex 3D structures that constantly change shape and interact with each other. Mapping out the many possible ways that proteins can be structured helps scientists understand how biological processes work, and may inform drug development and treating diseases such as cancer.

    Thanks to decades of research worldwide, we now have reliable, evidence-based 3D structures for tens of thousands of proteins, plus more than 100 million models of protein structures.

    These models are useful for learning about life’s molecular processes – such as how RNA and proteins are made – however, the large number of models can make it difficult for scientists to pin down which specific models can help answer a particular research question.

    To address this difficulty, one of us (Seán O’Donoghue) and colleagues developed Aquaria, a tool using the visualisation principle of “overview first, details on demand”. By using a technique called “clustering”, Aquaria creates a concise visual overview of all structural models available for any specific protein.

    2
    An overview of all 3D structural models available for p53, a protein that protects against cancer. Image created using Aquaria. S.I. O’Donoghue and C. Stolte, Author provided.

    The image above shows this overview for p53, a protein that protects against cancer. Each cluster of related 3D models can be interactively expanded and explored (bottom of the image), helping scientists find the most useful models suited to address a specific research question.

    Once a suitable model is found it is shown (top of the image), with dark colouring used to indicate regions where the structure of the model is less certain. In addition, yellow, blue and green are used to highlight different shapes within the structure, which helps scientists understand how the protein is arranged in three dimensions.

    Viewing connections between different datasets

    Sometimes, we need to look at data from multiple viewpoints. This is particularly true for a field of research known as sequencing. Sequencing involves determining the precise order of the chemical building blocks that make up DNA, RNA and protein. Knowing these sequences and comparing how they vary between individuals can tell us about mutations that cause disease and reveal how we evolved.

    One of the most widely used tools for visualising sequences is Jalview, co-developed by one of us (James Procter), which brings together the huge amounts of data that are created through sequencing.

    Jalview employs two principles – “linking and brushing” and “multiple coordinated views” – to bring together different types of information. Jalview also allows other tools to be connected, enabling scientists to navigate through complex, interrelated datasets.

    The example below shows a family of proteins known as Aquaporins, which are molecular channels important for water balance and nutrient transport in cells. Aligning these protein’s sequences (close up on right) allows them to be clustered into a tree (shown top-left, with birds-eye view of the protein alignment next door). DNA mutations are mapped onto the protein alignment (shown in red), and these colours also locate the mutations in protein structure (bottom left).

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    Linked brushing and multiple data visualisations allow potential disease mutations to be identified at the core of Aquaporin, a protein important for water balance and nutrient transport. Image created using Jalview linked with UCSF Chimera. J.B. Procter, Author provided.

    Visualising networks that change over time

    Scientists are aiming to unravel diseases – such as obesity – by studying small changes that take place within our cells.

    For example, food that we eat triggers the release of insulin into our blood stream, which then tells fat cells to store rather than release energy. This process ultimately influences our body weight.

    Cells are tiny, but they are hives of activity. Thanks to recent advances in techniques such as mass spectrometry, we can now map the tens of thousands of events that are happening within each of our cells in response to hormones such as insulin.

    The difficulty for scientists is to try to view this huge amount of information in an accurate and simple way, and one that reflects the chain of events in a cell that matter to our overall health.

    One of us (Seán O’Donoghue) and colleagues developed Minardo, an approach that creates a sort of timeline of events that happen inside a cell. Minardo uses the principle that position on a viewing screen is the most effective visualisation strategy. The resulting visualisation helps scientists identify exactly what is going on inside a healthy cell, and what might be different in a diseased cell.

    The image here shows (beginning top left, then clockwise) the sequence of events that take place after insulin (in pink) binds to the surface of a fat cell. The consequences of insulin binding include switching off the release of energy stores from the cell (around 1 minute after insulin binds), and switching on energy storage (around 5 minutes after insulin binds).

    5
    The sequence of key events within a human fat cell following insulin binding to its receptor (top left, pink). Image created using Minardo. D.K.G. Ma, C. Stolte, J.R. Krycer, D.E. James, and S.I. O’Donoghue, Author provided.

    VIZBI, an international visualisation community

    In building these tools, we aim to visualise data as clearly as possible, so the viewer can focus on the science.

    Aquaria, Jalview and Minardo are freely accessible and used by tens of thousands of scientists and students worldwide – an accomplishment that we are proud of.

    However, our tools address only three specific research questions – biology has thousands more. Tailored visualisations of this kind need an interdisciplinary team, take months to prototype and require years to develop into robust and usable tools.

    Realising this, in 2010, we created an international initiative called VIZBI to connect tool-builders and raise the standard of data visualisation in biology. In June 2017, VIZBI and associated events came to the Asia-Pacific region for the first time.

    The overwhelming complexity of biological data, substantial time and effort is required to create effective visualisation tools not just for communication but also for research itself.

    Seán I. O’Donoghue, Senior Faculty Member at the Garvan Institute, Conjoint Professor at UNSW, and Senior Principal Research Scientist, CSIRO and James B. Procter, Jalview Coordinator, Bioinformatician and Open Source Software Developer, University of Dundee

    See the full article here .

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    CSIRO campus

    CSIRO, the Commonwealth Scientific and Industrial Research Organisation, is Australia’s national science agency and one of the largest and most diverse research agencies in the world.

     
  • richardmitnick 1:59 pm on January 4, 2017 Permalink | Reply
    Tags: , Mass spectrometry, Proteases, Scripps Florida Scientists Expand Toolbox to Study Cellular Function,   

    From Scripps: “Scripps Florida Scientists Expand Toolbox to Study Cellular Function” 

    Scripps
    Scripps Research Institute

    January 4, 2017
    No writer credit

    Scientists on the Florida campus of The Scripps Research Institute (TSRI) have developed a new tool for studying the molecular details of protein structure.

    Their new study, published recently in the journal Proceedings of the National Academy of Sciences, explores how evolution can be used to discover new and useful enzyme tools, called proteases. Proteases cleave proteins into smaller peptide pieces that scientists can then analyze to determine the identity of the protein and whether a cell has made chemical changes to the protein that might alter its function.

    The new protease developed in the study helps shed light on these chemical changes, called post-translational modifications. Post-translational modifications are alterations made to proteins after the proteins are translated from RNA.

    “We have to observe these protein modifications directly through chemical analysis; we can’t read them out of DNA sequence,” explained study senior author Brian M. Paegel, associate professor at TSRI.

    These modifications can dramatically alter a protein’s stability and function, and unregulated modification can lead to disease, such as cancer. Therefore, understanding the nature and location of these modifications can be critical in the early phases of drug discovery.

    Scientists currently rely on a technique called mass spectrometry to study post-translational modifications. Mass spectrometry analyzes peptides to see if their mass changes—a bit like zooming in on that protein to see hidden details. An unexpected change in mass can indicate the occurrence of a post-translational modification.

    Many scientists today use a protease called trypsin to break proteins into peptides. Because there are few other proteases available for mass spectrometry, trypsin has become the workhorse of the field. However, Paegel explained, it’s luck of the draw if trypsin generates a peptide with a modified site. So Paegel and co-workers thought it would be useful to have a new tool that cleaved directly at the modified site.

    To solve this problem, Paegel developed a new trypsin “mutant” using a technique called “directed evolution.” The scientists created many thousands of trypsin mutants and tested each mutant for its ability to cut a protein at modified sites. They discovered a mutant that could cut proteins at citrulline, which is one type of modification.

    Paegel believes this new approach could be useful for mapping a wider range of post-translational modifications, and he hopes to use directed evolution to discover proteases that target many other post-translational modifications. “I think we’re on the brink of an explosion of new tools for mass spectrometry,” he said.

    In addition to Paegel, authors of the study, “Evolution of a mass spectrometry-grade protease with PTM-directed specificity,” were Duc. T. Tran (first author), Valerie Cavett, Vuong Q. Dang and Héctor L. Torres of TSRI.

    This study was supported by a National Institutes of Health’s Director’s New Innovator Award (grant OD008535) and a National Science Foundation Research Experiences for Undergraduates Grant (1359369).

    See the full article here .

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    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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