Eric J. Alm

About

Eric J. Alm is a professor at the Massachusetts Institute of Technology in the Department of Civil and Environmental Engineering. His research group employs both computational/theoretical and experimental approaches to understand the evolution of microorganisms, emphasizing a systems-level perspective. His areas of special interest include tools for detecting natural selection in microbes, the evolutionary origin of gene families, mining metagenomic sequence data, experimental evolution of microbes, modeling bacterial ecology, gene regulatory networks in bacteria, and protein structure and design. Professor Alm has a diverse academic background, holding a B.S. from the University of Illinois, Urbana, an M.S. from the University of California, Riverside, and a Ph.D. from the University of Washington, Seattle. He completed a postdoctoral fellowship at the University of California, Berkeley, and Lawrence Berkeley National Laboratory. He has enjoyed teaching a variety of classes at MIT, covering microbiology, computer algorithms, and thermodynamics of biomolecules, and is currently looking forward to teaching a new class on microbial evolution and genetics.

Research topics

• Biology
• Genetics
• Computer Science
• Microbiology
• Computational biology
• Virology
• Environmental engineering
• Artificial Intelligence
• Environmental science
• Data Mining

Selected publications

• SARS-CoV-2 Titers in Wastewater Are Higher than Expected from Clinically Confirmed Cases

  mSystems · 2020 · 875 citations

  Senior authorCorresponding

  Wastewater-based surveillance is a promising approach for proactive outbreak monitoring. SARS-CoV-2 is shed in stool early in the clinical course and infects a large asymptomatic population, making it an ideal target for wastewater-based monitoring. In this study, we develop a laboratory protocol to quantify viral titers in raw sewage via qPCR analysis and validate results with sequencing analysis. Our results suggest that the number of positive cases estimated from wastewater viral titers is or…

  DOI

• Wastewater-Based Epidemiology: Global Collaborative to Maximize Contributions in the Fight Against COVID-19

  Environmental Science & Technology · 2020 · 467 citations

  From the article: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel member of the Coronaviridae family, has been identified as the etiologic agent of an ongoing pandemic of severe pneumonia known as COVID-19. To date there have been millions of cases of COVID-19 diagnosed in 184 countries with case fatality rates ranging from 1.8% in Germany to 12.5% in Italy. Limited diagnostic testing capacity and asymptomatic and oligosymptomatic infections result in significant uncertaint…

  DOI

• High-throughput, single-microbe genomics with strain resolution, applied to a human gut microbiome

  Science · 2022 · 276 citations

  . Microbe-seq contributes high-throughput culture-free capabilities to investigate genomic blueprints of complex microbial communities with single-microbe resolution.

  PublisherOA PDFDOI

• A conserved Bacteroidetes antigen induces anti-inflammatory intestinal T lymphocytes

  Science · 2022 · 100 citations

  T cells that can differentiate into CD4IELs remains unknown. We identified β-hexosaminidase, a conserved enzyme across commensals of the Bacteroidetes phylum, as a driver of CD4IEL differentiation. In a mouse model of colitis, β-hexosaminidase-specific lymphocytes protected against intestinal inflammation. Thus, T cells of a single specificity can recognize a variety of abundant commensals and elicit a regulatory immune response at the intestinal mucosa.

  PublisherOA PDFDOI

• Predicting human health from biofluid-based metabolomics using machine learning

  Scientific Reports · 2020 · 38 citations

  Senior authorCorresponding

  Biofluid-based metabolomics has the potential to provide highly accurate, minimally invasive diagnostics. Metabolomics studies using mass spectrometry typically reduce the high-dimensional data to only a small number of statistically significant features, that are often chemically identified-where each feature corresponds to a mass-to-charge ratio, retention time, and intensity. This practice may remove a substantial amount of predictive signal. To test the utility of the complete feature set, w…

  PublisherOA PDFDOI

Recent grants

• Assembling the Tree of Life: Can Phylogenomics Resolve Deep Phylogeny?

  NSF · $1.3M · 2009–2014

• MSB: Genomics of Ecologically Defined Bacterial Populations

  NSF · $894k · 2009–2012

Frequent coauthors

• Janelle R. Thompson

  Singapore Centre for Environmental Life Sciences Engineering

  229 shared

• Xiaoqiong Gu

  National University of Singapore

  165 shared

• Wei Lin Lee

  Singapore-HUJ Alliance for Research and Enterprise

  163 shared

• Federica Armas

  Singapore-MIT Alliance for Research and Technology

  143 shared

• Adam P. Arkin

  University of California, Berkeley

  126 shared

• Hongjie Chen

  Nanfang Hospital

  123 shared

• Franciscus Chandra

  115 shared

• Ramnik J. Xavier

  Broad Institute

  106 shared

Education

• Ph.D., Microbiology

  Massachusetts Institute of Technology

  1994

• B.S., Microbiology

  University of California, Berkeley

  1989

Similar researchers at Massachusetts Institute of Technology

• Markus J. Buehlerh-121
• Dara Entekhabih-94
• Jesse Krollh-90