Biology subjects

Price, M. N.

Publications and source records attributed to Price, M. N..

27 records · Page 2Linked to original sources

bioRxiv2020

High-throughput mapping of the phage resistance landscape in E. coli

Bacteriophages (phages) are critical players in the dynamics and function of microbial communities and drive processes as diverse as global biogeochemical cycles and human health. Phages tend to be predators finely tuned to attack specific hosts, even down to the strain level, which in turn defend themselves using an array of mechanisms. However, to date, efforts to rapidly and comprehensively identify bacterial host factors important in phage infection and resistance have yet to be fully realized. Here, we globally map the host genetic determinants involved in resistance to 14 phylogenetically diverse double-stranded DNA phages using two model Escherichia coli strains (K-12 and BL21) with known sequence divergence to demonstrate strain-specific differences. Using genome-wide loss-of-function and gain-of-function genetic technologies, we are able to confirm previously described phage receptors as well as uncover a number of previously unknown host factors that confer resistance to one or more of these phages. We uncover differences in resistance factors that strongly align with the susceptibility of K-12 and BL21 to specific phage. We also identify both phage specific mechanisms, such as the unexpected role of cyclic-di-GMP in host sensitivity to phage N4, and more generic defenses, such as the overproduction of colanic acid capsular polysaccharide that defends against a wide array of phages. Our results indicate that host responses to phages can occur via diverse cellular mechanisms. Our systematic and high-throughput genetic workflow to characterize phage-host interaction determinants can be extended to diverse bacteria to generate datasets that allow predictive models of how phage-mediated selection will shape bacterial phenotype and evolution. The results of this study and future efforts to map the phage resistance landscape will lead to new insights into the coevolution of hosts and their phage, which can ultimately be used to design better phage therapeutic treatments and tools for precision microbiome engineering.

microbiology↗

bioRxiv2019

Selective carbon sources influence the end-products of microbial nitrate respiration

Respiratory and catabolic pathways are differentially distributed in microbial genomes. Thus, specific carbon sources may favor different respiratory processes. We profiled the influence of 94 carbon sources on the end-products of nitrate respiration in microbial enrichment cultures from diverse terrestrial environments. We found that some carbon sources consistently favor dissimilatory nitrate reduction to ammonium (DNRA/nitrate ammonification) while other carbon sources favor nitrite accumulation or denitrification. For an enrichment culture from aquatic sediment, we sequenced the genomes of the most abundant strains, matched these genomes to 16S rDNA exact sequence variants (ESVs), and used 16S rDNA amplicon sequencing to track the differential enrichment of functionally distinct ESVs on different carbon sources. We found that changes in the abundances of strains with different genetic potentials for nitrite accumulation, DNRA or denitrification were correlated with the nitrite or ammonium concentrations in the enrichment cultures recovered on different carbon sources. Specifically, we found that either L-sorbose or D-cellobiose enriched for a Klebsiella nitrite accumulator, other sugars enriched for an Escherichia nitrate ammonifier, and citrate or formate enriched for a Pseudomonas denitrifier and a Sulfurospirillum nitrate ammonifier. Our results add important nuance to the current paradigm that higher concentrations of carbon will always favor DNRA over denitrification or nitrite accumulation, and we propose that, in some cases, carbon composition can be as important as carbon concentration in determining nitrate respiratory end-products. Furthermore, our approach can be extended to other environments and metabolisms to characterize how selective parameters influence microbial community composition, gene content and function.

microbiology↗

bioRxiv2019

GapMind: Automated annotation of amino acid biosynthesis

GapMind is a web-based tool for annotating amino acid biosynthesis in bacteria and archaea (http://papers.genomics.lbl/gov/gaps). GapMind incorporates many variant pathways and 130 different reactions, and it analyzes a genome in just 15 seconds. To avoid error-prone \"transitive\" annotations, GapMind relies primarily on a database of experimentally-characterized proteins. GapMind correctly handles fusion proteins and split proteins, which often cause errors for \"best hit\" approaches. To improve GapMinds coverage, we examined genetic data from 35 bacteria that grow in minimal media and we filled many gaps in amino acid biosynthesis pathways. For example, we identified additional genes for arginine synthesis with succinylated intermediates in Bacteroides thetaiotaomicron and we propose that Dyella japonica synthesizes tyrosine from phenylalanine. Nevertheless, for many bacteria and archaea that grow in minimal media, genes for some steps still cannot be identified. If a potential gap in the genome of interest is also a gap in a related microbe that can grow in minimal media, GapMind marks the gap as \"known.\"

bioinformatics↗

bioRxiv2019

Large-scale chemical-genetics of the human gut bacterium Bacteroides thetaiotaomicron

The genomic catalogue of the human microbiota has expanded dramatically in recent years, and insights derived from human microbiota genomics has vast potential to generate treatments for human diseases. However, predictably harnessing the microbiota for beneficial outcomes is currently limited by our lack of understanding of the physiology of the constituent bacteria. For instance, the functions of most of their genes are not known. Here, we systematically measure mutant phenotypes for genes from the gut commensal Bacteroides thetaiotaomicron. Using a barcoded transposon mutant library, we measured the fitness of 4,055 B. thetaiotaomicron genes across 492 experiments, including growth on 45 carbon substrates and in the presence of 57 stress-inducing compounds. Our data is in strong agreement with previous studies, and more importantly also uncovers the biological roles of poorly annotated genes. We identified 497 genes with a specific phenotype in only one or a handful of conditions, thus enabling informed predictions of gene function for a subset of these genes. For example, we identified a glycoside hydrolase important for growth on type I rhamnogalacturonan, a DUF4861 protein for glycosaminoglycan utilization, a DUF1080 protein for disaccharide utilization, and a tripartite multidrug resistance system specifically important for bile salt tolerance. Our approach can be applied to other members of the human microbiota to experimentally characterize their genes.

microbiology↗

bioRxiv2018

Defining the toxicity limits on microbial range in a metal-contaminated aquifer

In extreme environments, toxic compounds restrict which microorganisms persist. However, in complex mixtures of inhibitory compounds, it is challenging to determine which specific compounds cause changes in abundance and prevent some microorganisms from growing. We focused on a contaminated aquifer in Oak Ridge, Tennessee, U.S.A. that has low pH and high concentrations of uranium, nitrate and many other inorganic ions. In the most contaminated wells, the microbial community is enriched in the Rhodanobacter genus. Rhodanobacter relative abundance is positively correlated with low pH and high concentrations of U, Mn, Al, Cd, Zn, Ni, Co, Ca, NO3-, Mg, Cl, SO42-, Sr, K and Ba and we sought to determine which of these correlated parameters are selective pressures that favor the growth of Rhodanobacter over other taxa. Using high-throughput cultivation, we determined that of the ions correlated high Rhodanobacter abundance, only low pH and high U, Mn, Al, Cd, Zn, Co and Ni (a) are selectively inhibitory of a sensitive Pseudomonas isolate from a background well versus a representative resistant Rhodanobacter isolate from a contaminated well, and (b) reach toxic concentrations in the most contaminated wells that can inhibit the sensitive Pseudomonas isolate. We prepared mixtures of inorganic ions representative of the most contaminated wells and verified that few other isolates aside from Rhodanobacter can tolerate these 8 parameters. These results clarify which toxic inorganic ions are causal factors that impact the microbial community at this field site and are not merely correlated with taxonomic shifts.

microbiology↗

bioRxiv2018

Dub-seq: dual-barcoded shotgun expression library sequencing for high-throughput characterization of functional traits

A major challenge in genomics is the knowledge gap between sequence and its encoded function. Gain-of-function methods based on gene overexpression are attractive avenues for phenotype-based functional screens, but are not easily applied in high-throughput across many experimental conditions. Here, we present Dual Barcoded Shotgun Expression Library Sequencing (Dub-seq), a method that greatly increases the throughput of genome-wide overexpression assays. In Dub-seq, a shotgun expression library is cloned between dual random DNA barcodes and the precise breakpoints of DNA fragments are associated to the barcode sequences prior to performing assays. To assess the fitness of individual strains carrying these plasmids, we use DNA barcode sequencing (BarSeq), which is amenable to large-scale sample multiplexing. As a demonstration of this approach, we constructed a Dub-seq library with total Escherichia coli genomic DNA, performed 155 genome-wide fitness assays in 52 experimental conditions, and identified 813 genes with high-confidence overexpression phenotypes across 4,151 genes assayed. We show that Dub-seq data is reproducible, accurately recapitulates known biology, and identifies hundreds of novel gain-of-function phenotypes for E. coli genes, a subset of which we verified with assays of individual strains. Dub-seq provides complementary information to loss-of-function approaches such as transposon site sequencing or CRISPRi and will facilitate rapid and systematic functional characterization of microbial genomes.\n\nImportanceMeasuring the phenotypic consequences of overexpressing genes is a classic genetic approach for understanding protein function; for identifying drug targets, antibiotic and metal resistance mechanisms; and for optimizing strains for metabolic engineering. In microorganisms, these gain-of-function assays are typically done using laborious protocols with individually archived strains or in low-throughput following qualitative selection for a phenotype of interest, such as antibiotic resistance. However, many microbial genes are poorly characterized and the importance of a given gene may only be apparent under certain conditions. Therefore, more scalable approaches for gain-of-function assays are needed. Here, we present Dual Barcoded Shotgun Expression Library Sequencing (Dub-seq), a strategy that couples systematic gene overexpression with DNA barcode sequencing for large-scale interrogation of gene fitness under many experimental conditions at low cost. Dub-seq can be applied to many microorganisms and is a valuable new tool for large-scale gene function characterization.

microbiology↗

bioRxiv2017

An Oxidative Pathway of Deoxyribose Catabolism

Using genome-wide mutant fitness assays in diverse bacteria, we identified novel oxidative pathways for the catabolism of 2-deoxy-D-ribose and 2-deoxy-D-ribonate. We propose that deoxyribose is oxidized to deoxyribonate, oxidized to ketodeoxyribonate, and cleaved to acetyl-CoA and glyceryl-CoA. We have genetic evidence for this pathway in three genera of bacteria, and we confirmed the oxidation of deoxyribose to ketodeoxyribonate in vitro. In Pseudomonas simiae, the expression of enzymes in the pathway is induced by deoxyribose or deoxyribonate, while in Paraburkholderia bryophila and in Burkholderia phytofirmans, the pathway proceeds in parallel with the known deoxyribose 5-phosphate aldolase pathway. We identified another oxidative pathway for the catabolism of deoxyribonate, with acyl-CoA intermediates, in Klebsiella michiganensis. Of these four bacteria, only P. simiae relies entirely on an oxidative pathway to consume deoxyribose. The deoxyribose dehydrogenase of P. simiae is either non-specific or evolved recently, as this enzyme is very similar to a novel vanillin dehydrogenase from Pseudomonas putida that we identified. So, we propose that these oxidative pathways evolved primarily to consume deoxyribonate, which is a waste product of metabolism.\n\nImportanceDeoxyribose is one of the building blocks of DNA and is released when cells die and their DNA degrades. We identified a bacterium that can grow with deoxyribose as its sole source of carbon even though its genome does not encode any of the known genes for breaking down deoxyribose. By growing many mutants of this bacterium together on deoxyribose and using DNA sequencing to measure the change in the mutants abundance, we identified multiple protein-coding genes that are required for growth on deoxyribose. Based on the similarity of these proteins to enzymes of known function, we propose a 6-step pathway in which deoxyribose is oxidized and then cleaved. Diverse bacteria use a portion of this pathway to break down a related compound, deoxyribonate, which is a waste product of human metabolism and is present in urine. Our study illustrates the utility of large-scale bacterial genetics to identify previously unknown metabolic pathways.

microbiology↗

bioRxiv2017

PaperBLAST: Text-mining papers for information about homologs

Large-scale genome sequencing has identified millions of protein-coding genes whose function is unknown. Many of these proteins are similar to characterized proteins from other organisms, but much of this information is missing from annotation databases and is hidden in the scientific literature. To make this information accessible, PaperBLAST uses EuropePMC to search the full text of scientific articles for references to genes. PaperBLAST also takes advantage of curated resources that link protein sequences to scientific articles (Swiss-Prot, GeneRIF, and EcoCyc). PaperBLASTs database includes over 700,000 scientific articles that mention over 400,000 different proteins. Given a protein of interest, PaperBLAST quickly finds similar proteins that are discussed in the literature and presents snippets of text from relevant articles or from the curators. PaperBLAST is available at http://papers.genomics.lbl.gov/.

bioinformatics↗

bioRxiv2016

Validating Regulatory Predictions from Diverse Bacteria with Mutant Fitness Data

Although transcriptional regulation is fundamental to understanding bacterial physiology, the targets of most bacterial transcription factors are not known. Comparative genomics has been used to identify likely targets of some of these transcription factors, but these predictions typically lack experimental support. Here, we used mutant fitness data, which measures the importance of each gene for a bacteriums growth across many conditions, to validate regulatory predictions from RegPrecise, a curated collection of comparative genomics predictions. Because characterized transcription factors often have correlated fitness with one of their targets (either positively or negatively), correlated fitness patterns provide support for the comparative genomics predictions. At a false discovery rate of 3%, we identified significant cofitness for at least one target of 158 TFs in 107 ortholog groups and from 24 bacteria. Thus, high-throughput genetics can be used to identify a high-confidence subset of the sequence-based regulatory predictions.

microbiology↗