Michael Fischbach

Last updated
Michael Fischbach
Born(1980-11-03)November 3, 1980
Alma mater
Scientific career
Institutions
Website fischbachgroup.org

Michael Andrew Fischbach (born November 3, 1980) is an American chemist, microbiologist, and geneticist. He is an associate professor of Bioengineering and ChEM-H Faculty Fellow at Stanford University [1] [2] and a Chan Zuckerberg Biohub Investigator. [3]

Contents

Education

Fischbach earned his A.B. in Biochemical Sciences from Harvard College in 2003. During that time (2000-2003), he worked in Jeffrey Settleman's lab at the Massachusetts General Hospital Cancer Center on the biochemistry of oncogenic mutants of the small GTPase Ras. [4] In 2007, he earned his Ph.D. in Chemistry and Chemical Biology from Harvard University, working in Christopher T. Walsh's laboratory at Harvard Medical School on iron acquisition in bacterial pathogens and the biochemistry of natural product biosynthesis. [5] [6]

Career

Fischbach was a junior fellow in the Department of Molecular Biology at Massachusetts General Hospital (2007-2009) before joining the faculty of the University of California, San Francisco in 2009. He moved to Stanford University as an associate professor in September 2017. As a Chan Zuckerberg Biohub Investigator, Fischbach is one of eight faculty members across Stanford, UCSF, and the University of California, Berkeley leading the CZ Biohub Microbiome Initiative, launched in 2018, with the goal of understanding how the microbiota can influence human health. [7]

Fischbach is currently a member of the scientific advisory board of NGM Biopharmaceuticals [8] and a co-founder of Revolution Medicines. [9]

Research

Fischbach's lab focuses on discovering and characterizing small molecules from microorganisms, with an emphasis on the human microbiome. [10] [11]

Small molecules from the human microbiota

In 2014, Fischbach and his laboratory published a survey of biosynthetic genes in the human microbiome, describing the ability of human-associated microbes to produce thiopeptide antibiotics. [12] [13] [14] [15] The Fischbach lab discovered that the gut commensal Bacteroides fragilis produces the immune modulatory sphingolipid alpha-galactosylceramide, [16] showed that the production of neurotransmitters is common among commensal gut bacteria, [17] and discovered the biosynthetic pathway for a common class of bile acids produced by gut bacteria. [18]

Computational approaches to natural product discovery

Fischbach's lab developed an algorithm, ClusterFinder, that automates the process of identifying biosynthetic genes for small molecules in bacterial genome sequences. [19] [20] With Marnix Medema, he co-developed a second algorithm for identifying biosynthetic gene clusters, antiSMASH, [21] with which ClusterFinder has been merged.

Personal life

Fischbach is married to Elizabeth Sattely, Associate Professor of Chemical Engineering at Stanford. [22]

Related Research Articles

<span class="mw-page-title-main">Human microbiome</span> Microorganisms in or on human skin and biofluids

The human microbiome is the aggregate of all microbiota that reside on or within human tissues and biofluids along with the corresponding anatomical sites in which they reside, including the skin, mammary glands, seminal fluid, uterus, ovarian follicles, lung, saliva, oral mucosa, conjunctiva, biliary tract, and gastrointestinal tract. Types of human microbiota include bacteria, archaea, fungi, protists and viruses. Though micro-animals can also live on the human body, they are typically excluded from this definition. In the context of genomics, the term human microbiome is sometimes used to refer to the collective genomes of resident microorganisms; however, the term human metagenome has the same meaning.

<span class="mw-page-title-main">Clostridia</span> Class of bacteria

The Clostridia are a highly polyphyletic class of Bacillota, including Clostridium and other similar genera. They are distinguished from the Bacilli by lacking aerobic respiration. They are obligate anaerobes and oxygen is toxic to them. Species of the class Clostridia are often but not always Gram-positive and have the ability to form spores. Studies show they are not a monophyletic group, and their relationships are not entirely certain. Currently, most are placed in a single order called Clostridiales, but this is not a natural group and is likely to be redefined in the future.

Computational genomics refers to the use of computational and statistical analysis to decipher biology from genome sequences and related data, including both DNA and RNA sequence as well as other "post-genomic" data. These, in combination with computational and statistical approaches to understanding the function of the genes and statistical association analysis, this field is also often referred to as Computational and Statistical Genetics/genomics. As such, computational genomics may be regarded as a subset of bioinformatics and computational biology, but with a focus on using whole genomes to understand the principles of how the DNA of a species controls its biology at the molecular level and beyond. With the current abundance of massive biological datasets, computational studies have become one of the most important means to biological discovery.

<span class="mw-page-title-main">Gut microbiota</span> Community of microorganisms in the gut

Gut microbiota, gut microbiome, or gut flora, are the microorganisms, including bacteria, archaea, fungi, and viruses that live in the digestive tracts of animals. The gastrointestinal metagenome is the aggregate of all the genomes of the gut microbiota. The gut is the main location of the human microbiome. The gut microbiota has broad impacts, including effects on colonization, resistance to pathogens, maintaining the intestinal epithelium, metabolizing dietary and pharmaceutical compounds, controlling immune function, and even behavior through the gut–brain axis.

<i>Bacteroides</i> Genus of bacteria

Bacteroides is a genus of Gram-negative, obligate anaerobic bacteria. Bacteroides species are non endospore-forming bacilli, and may be either motile or nonmotile, depending on the species. The DNA base composition is 40–48% GC. Unusual in bacterial organisms, Bacteroides membranes contain sphingolipids. They also contain meso-diaminopimelic acid in their peptidoglycan layer.

Dysbiosis is characterized by a disruption to the microbiome resulting in an imbalance in the microbiota, changes in their functional composition and metabolic activities, or a shift in their local distribution. For example, a part of the human microbiota such as the skin flora, gut flora, or vaginal flora, can become deranged, with normally dominating species underrepresented and normally outcompeted or contained species increasing to fill the void. Dysbiosis is most commonly reported as a condition in the gastrointestinal tract.

<span class="mw-page-title-main">Skin flora</span> Microbiota that reside on the skin

Skin flora, also called skin microbiota, refers to microbiota that reside on the skin, typically human skin.

The resistome has been used to describe to two similar yet separate concepts:

Methanobrevibacter smithii is the predominant archaeon in the microbiota of the human gut. M. smithii has a coccobacillus shape. It plays an important role in the efficient digestion of polysaccharides by consuming the end products of bacterial fermentation. Methanobrevibacter smithii is a single-celled microorganism from the Archaea domain. M. smithii is a methanogen, and a hydrogenotroph that recycles the hydrogen by combining it with carbon dioxide to methane. The removal of hydrogen by M. smithii is thought to allow an increase in the extraction of energy from nutrients by shifting bacterial fermentation to more oxidized end products.

<span class="mw-page-title-main">Human Microbiome Project</span> Former research initiative

The Human Microbiome Project (HMP) was a United States National Institutes of Health (NIH) research initiative to improve understanding of the microbiota involved in human health and disease. Launched in 2007, the first phase (HMP1) focused on identifying and characterizing human microbiota. The second phase, known as the Integrative Human Microbiome Project (iHMP) launched in 2014 with the aim of generating resources to characterize the microbiome and elucidating the roles of microbes in health and disease states. The program received $170 million in funding by the NIH Common Fund from 2007 to 2016.

<span class="mw-page-title-main">Microbiota</span> Community of microorganisms

Microbiota are the range of microorganisms that may be commensal, symbiotic, or pathogenic found in and on all multicellular organisms, including plants. Microbiota include bacteria, archaea, protists, fungi, and viruses, and have been found to be crucial for immunologic, hormonal, and metabolic homeostasis of their host.

Microbiota-accessible carbohydrates (MACs) are carbohydrates that are resistant to digestion by a host's metabolism, and are made available for gut microbes, as prebiotics, to ferment or metabolize into beneficial compounds, such as short chain fatty acids. The term, ‘‘microbiota-accessible carbohydrate’’ contributes to a conceptual framework for investigating and discussing the amount of metabolic activity that a specific food or carbohydrate can contribute to a host's microbiota.

<span class="mw-page-title-main">Lactocillin</span> Chemical compound

Lactocillin is a thiopeptide antibiotic which is encoded for and produced by biosynthetic genes clusters in the bacteria Lactobacillus gasseri. Lactocillin was discovered and purified in 2014. Lactobacillus gasseri is one of the four Lactobacillus bacteria found to be most common in the human vaginal microbiome. Due to increasing levels of pathogenic resistance to known antibiotics, novel antibiotics are increasingly valuable. Lactocillin could function as a new antibiotic that could help people fight off infections that are resistant to many other antibiotics.

Metatranscriptomics is the set of techniques used to study gene expression of microbes within natural environments, i.e., the metatranscriptome.

The microbiota are the sum of all symbiotic microorganisms living on or in an organism. The fruit fly Drosophila melanogaster is a model organism and known as one of the most investigated organisms worldwide. The microbiota in flies is less complex than that found in humans. It still has an influence on the fitness of the fly, and it affects different life-history characteristics such as lifespan, resistance against pathogens (immunity) and metabolic processes (digestion). Considering the comprehensive toolkit available for research in Drosophila, analysis of its microbiome could enhance our understanding of similar processes in other types of host-microbiota interactions, including those involving humans. Microbiota plays key roles in the intestinal immune and metabolic responses via their fermentation product, acetate.

<span class="mw-page-title-main">David Relman</span> American microbiologist

David Arnold Relman is an American microbiologist and the Thomas C. and Joan M. Merigan Professor in Medicine, and in Microbiology & Immunology at the Stanford University School of Medicine. His research focuses on the human microbiome and microbial ecosystem—for which he was a pioneer in the use of modern molecular methods, as well as on pathogen discovery and the genomics of host response.

<span class="mw-page-title-main">Pharmacomicrobiomics</span>

Pharmacomicrobiomics, first proposed by Prof. Marco Candela for the ERC-2009-StG project call and later publicly used in 2010, is defined as the effect of microbiome variations on drug disposition, action, and toxicity. Pharmacomicrobiomics is concerned with the interaction between xenobiotics, or foreign compounds, and the gut microbiome. It is estimated that over 100 trillion prokaryotes representing more than 1000 species reside in the gut. Within the gut, microbes help modulate developmental, immunological and nutrition host functions. The aggregate genome of microbes extends the metabolic capabilities of humans, allowing them to capture nutrients from diverse sources. Namely, through the secretion of enzymes that assist in the metabolism of chemicals foreign to the body, modification of liver and intestinal enzymes, and modulation of the expression of human metabolic genes, microbes can significantly impact the ingestion of xenobiotics.

Machine learning in bioinformatics is the application of machine learning algorithms to bioinformatics, including genomics, proteomics, microarrays, systems biology, evolution, and text mining.

Metabolic gene clusters or biosynthetic gene clusters are tightly linked sets of mostly non-homologous genes participating in a common, discrete metabolic pathway. The genes are in physical vicinity to each other on the genome, and their expression is often coregulated. Metabolic gene clusters are common features of bacterial and most fungal genomes, and are less often found in other organisms. They are most widely known for producing secondary metabolites, which are the source or basis of most pharmaceutical compounds, natural toxins, and chemical communication and chemical warfare between organisms. Metabolic gene clusters are also involved in nutrient acquisition, toxin degradation, antimicrobial resistance, and vitamin biosynthesis. Given all these properties of metabolic gene clusters, they play a key role in shaping microbial ecosystems, including microbiome-host interactions. Thus several computational genomics tools have been developed to predict metabolic gene clusters.

<span class="mw-page-title-main">Genome mining</span>

Genome mining describes the exploitation of genomic information for the discovery of biosynthetic pathways of natural products and their possible interactions. It depends on computational technology and bioinformatics tools. The mining process relies on a huge amount of data accessible in genomic databases. By applying data mining algorithms, the data can be used to generate new knowledge in several areas of medicinal chemistry, such as discovering novel natural products.

References

  1. ↑ "Michael Fischbach's Profile | Stanford Profiles". profiles.stanford.edu. Retrieved 2019-07-12.
  2. ↑ "Faculty Fellows | ChEM-H". chemh.stanford.edu. Retrieved 2019-07-12.
  3. ↑ "Investigator Program – Chan Zuckerberg Biohub" . Retrieved 2019-07-12.
  4. ↑ Fischbach MA, Settleman J. Specific biochemical inactivation of oncogenic Ras proteins by nucleoside diphosphate kinase. Cancer Res. 2003 Jul 15;63(14):4089-94. PMID   12874011.
  5. ↑ Fischbach MA, Lin H, Liu DR, Walsh CT. In vitro characterization of IroB, a pathogen-associated C-glycosyltransferase. Proc Natl Acad Sci U S A. 2005 Jan 18;102(3):571-6. Epub 2004 Dec 14. PMID   15598734; PMC   545562.
  6. ↑ Walsh CT, Fischbach MA. Natural products version 2.0: connecting genes to molecules. J Am Chem Soc. 2010 Mar 3;132(8):2469-93. doi : 10.1021/ja909118a. PMID   20121095; PMC   2828520.
  7. ↑ "Chan Zuckerberg Biohub funds new research efforts, microbiome initiative". News Center. Retrieved 2019-07-12.
  8. ↑ "Scientific Advisory Board - NGM Bio". www.ngmbio.com. Archived from the original on 2018-07-20. Retrieved 2016-01-07.
  9. ↑ "Team - Revolution Medicines". revolutionmedicines.com.
  10. ↑ "Fischbach Group - Home". fischbachgroup.org.
  11. ↑ Donia MS, Fischbach MA. Small molecules from the human microbiota. Science. 2015 Jul 24;349(6246):1254766. doi : 10.1126/science.1254766. Epub 2015 Jul 23. Review. PMID   26206939; PMC   4641445
  12. ↑ Donia MS, Cimermancic P, Schulze CJ, Wieland Brown LC, Martin J, Mitreva M, Clardy J, Linington RG, Fischbach MA. A systematic analysis of biosynthetic gene clusters in the human microbiome reveals a common family of antibiotics. Cell. 2014 Sep 11;158(6):1402-14. doi : 10.1016/j.cell.2014.08.032. PMID   25215495; PMC   4164201.
  13. ↑ "Mining for Antibiotics, Right Under Our Noses". The New York Times. 2014-09-11.
  14. ↑ Park, Alice (2014-09-12). "DIY Drugs: Antibiotics Could Soon Be Made Out of Your Own Bacteria". Time. Retrieved 2018-04-26.
  15. ↑ "Set a thief... Humanity's bacterial companions are a good place to look for new drugs". The Economist. 2014-09-20. Retrieved 2018-04-26.
  16. ↑ Wieland Brown LC, Penaranda C, Kashyap PC, Williams BB, Clardy J, Kronenberg M, Sonnenburg JL, Comstock LE, Bluestone JA, Fischbach MA. Production of α-galactosylceramide by a prominent member of the human gut microbiota. PLoS Biol. 2013 Jul;11(7):e1001610. doi : 10.1371/journal.pbio.1001610. Epub 2013 Jul 16. PMID   23874157; PMC   3712910.
  17. ↑ Williams BB, Van Benschoten AH, Cimermancic P, Donia MS, Zimmermann M, Taketani M, Ishihara A, Kashyap PC, Fraser JS, Fischbach MA. Discovery and characterization of gut microbiota decarboxylases that can produce the neurotransmitter tryptamine. Cell Host Microbe. 2014 Oct 8;16(4):495-503. doi : 10.1016/j.chom.2014.09.001. Epub 2014 Sep 25. PMID   25263219; PMC   4260654.
  18. ↑ Devlin AS, Fischbach MA. A biosynthetic pathway for a prominent class of microbiota-derived bile acids. Nat Chem Biol. 2015 Sep;11(9):685-90. doi : 10.1038/nchembio.1864. Epub 2015 Jul 20. PMID   26192599; PMC   4543561.
  19. ↑ Cimermancic P, Medema MH, Claesen J, Kurita K, Wieland Brown LC, Mavrommatis K, Pati A, Godfrey PA, Koehrsen M, Clardy J, Birren BW, Takano E, Sali A, Linington RG, Fischbach MA. Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters. Cell. 2014 Jul 17;158(2):412-21. doi : 10.1016/j.cell.2014.06.034. PMID   25036635; PMC   4123684.
  20. ↑ Medema MH, Fischbach MA. Computational approaches to natural product discovery. Nat Chem Biol. 2015 Sep;11(9):639-48. doi : 10.1038/nchembio.1884. PMID   26284671.
  21. ↑ "antiSMASH bacterial version". antismash.secondarymetabolites.org.
  22. ↑ "Elizabeth Sattely's Profile | Stanford Profiles". profiles.stanford.edu. Retrieved 2019-07-12.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.