Magnitude and Dynamics of the T-Cell Response to SARS-CoV-2 Infection at Both Individual and Population Levels.

T cells are involved in the early identification and clearance of viral infections and also support the development of antibodies by B cells. This central role for T cells makes them a desirable target for assessing the immune response to SARS-CoV-2 infection. Here, we combined two high-throughput immune profiling methods to create a quantitative picture of the T-cell response to SARS-CoV-2. First, at the individual level, we deeply characterized 3 acutely infected and 58 recovered COVID-19 subjects by experimentally mapping their CD8 T-cell response through antigen stimulation to 545 Human Leukocyte Antigen (HLA) class I presented viral peptides (class II data in a forthcoming study). Then, at the population level, we performed T-cell repertoire sequencing on 1,815 samples (from 1,521 COVID-19 subjects) as well as 3,500 controls to identify shared "public" T-cell receptors (TCRs) associated with SARS-CoV-2 infection from both CD8 and CD4 T cells. Collectively, our data reveal that CD8 T-cell responses are often driven by a few immunodominant, HLA-restricted epitopes. As expected, the T-cell response to SARS-CoV-2 peaks about one to two weeks after infection and is detectable for at least several months after recovery. As an application of these data, we trained a classifier to diagnose SARS-CoV-2 infection based solely on TCR sequencing from blood samples, and observed, at 99.8% specificity, high early sensitivity soon after diagnosis (Day 3-7 = 85.1% [95% CI = 79.9-89.7]; Day 8-14 = 94.8% [90.7-98.4]) as well as lasting sensitivity after recovery (Day 29+/convalescent = 95.4% [92.1-98.3]). These results demonstrate an approach to reliably assess the adaptive immune response both soon after viral antigenic exposure (before antibodies are typically detectable) as well as at later time points. This blood-based molecular approach to characterizing the cellular immune response has applications in clinical diagnostics as well as in vaccine development and monitoring.

A Mutagenic Screen Identifies a TonB-Dependent Receptor Required for the Lanthanide Metal Switch in the Type I Methanotroph "Methylotuvimicrobium buryatense" 5GB1C.

Several of the metabolic enzymes in methanotrophic bacteria rely on metals for both their expression and their catalysis. The MxaFI methanol dehydrogenase enzyme complex uses calcium as a cofactor to oxidize methanol, while the alternative methanol dehydrogenase XoxF uses lanthanide metals such as lanthanum and cerium for the same function. Lanthanide metals, abundant in the earth's crust, strongly repress the transcription of mxaF yet activate the transcription of xoxF This regulatory program, called the "lanthanide switch," is central to methylotrophic metabolism, but only some of its components are known. To uncover additional components of the lanthanide switch, we developed a chemical mutagenesis system in the type I gammaproteobacterial methanotroph "Methylotuvimicrobium buryatense" 5GB1C and designed a selection system for mutants unable to repress the mxaF promoter in the presence of lanthanum. Whole-genome resequencing for multiple lanthanide switch mutants identified several unique point mutations in a single gene encoding a TonB-dependent receptor, which we have named LanA. The LanA TonB-dependent receptor is absolutely required for the lanthanide switch and controls the expression of a small set of genes. While mutation of the lanA gene does not affect the amount of cell-associated lanthanum, it is essential for growth in the absence of the MxaF methanol dehydrogenase, suggesting that LanA is involved in lanthanum uptake to supply the XoxF methanol dehydrogenase with its critical metal ion cofactor. The discovery of this novel component of the lanthanide regulatory system highlights the complexity of this circuit and suggests that further components are likely involved.IMPORTANCE Lanthanide metals, or rare earth elements, are abundant in nature and used heavily in technological devices. Biological interactions with lanthanides are just beginning to be unraveled. Until very recently, microbial mechanisms of lanthanide metal interaction and uptake were unknown. The TonB-dependent receptor LanA is the first lanthanum receptor identified in a methanotroph. Sequence homology searches with known metal transporters and regulators could not be used to identify LanA or other lanthanide metal switch components, and this method for mutagenesis and selection was required to identify the receptor. This work advances the knowledge of microbe-metal interactions in environmental niches that impact atmospheric methane levels and are thus relevant to climate change.

Adaptive Strategies of the Candidate Probiotic E. coli Nissle in the Mammalian Gut.

Probiotics are living microorganisms that are increasingly used as gastrointestinal therapeutics by virtue of their innate or engineered genetic function. Unlike abiotic therapeutics, probiotics can replicate in their intended site, subjecting their genomes and therapeutic properties to natural selection. We exposed the candidate probiotic E. coli Nissle (EcN) to the mouse gastrointestinal tract over several weeks, systematically altering the diet and background microbiota complexity. In-transit EcN accumulates genetic mutations that modulate carbohydrate utilization, stress response, and adhesion to gain competitive fitness, while previous exposure to antibiotics reveals an acquisition of resistance. We then leveraged these insights to generate an EcN strain that shows therapeutic efficacy in a mouse model of phenylketonuria and found that it was genetically stable over 1 week, thereby validating EcN's utility as a chassis for engineering. Collectively, we demonstrate a generalizable pipeline that can be applied to other probiotics to better understand their safety and engineering potential.

Interspecies Chemical Signaling in a Methane-Oxidizing Bacterial Community.

Multiple species of bacteria oxidize methane in the environment after it is produced by anaerobic ecosystems. These organisms provide reduced carbon substrates for species that cannot oxidize methane themselves, thereby serving a key role in these niches while also sequestering this potent greenhouse gas before it enters the atmosphere. Deciphering the molecular details of how methane-oxidizing bacteria interact in the environment enables us to understand an important aspect that shapes the structures and functions of these communities. Here we show that many members of the Methylomonas genus possess a LuxR-type acyl-homoserine lactone (acyl-HSL) receptor/transcription factor that is highly homologous to MbaR from the quorum-sensing (QS) system of Methylobacter tundripaludum, another methane oxidizer that has been isolated from the same environment. We reconstitute this detection system in Escherichia coli and use mutant and transcriptomic analysis to show that the receptor/transcription factor from Methylomonas sp. strain LW13 is active and alters LW13 gene expression in response to the acyl-HSL produced by M. tundripaludum These findings provide a molecular mechanism for how two species of bacteria that may compete for resources in the environment can interact in a specific manner through a chemical signal.IMPORTANCE Methanotrophs are bacteria that sequester methane, a significant greenhouse gas, and thereby perform an important ecosystem function. Understanding the mechanisms by which these organisms interact in the environment may ultimately allow us to manipulate and to optimize this activity. Here we show that members of a genus of methane-oxidizing bacteria can be influenced by a chemical signal produced by a possibly competing species. This provides insight into how gene expression can be controlled in these bacterial communities via an exogenous chemical signal.

Mosaic plasmids are abundant and unevenly distributed across prokaryotic taxa.

Mosaic plasmids, plasmids composed of genetic elements from distinct sources, are associated with the spread of antibiotic resistance genes. Transposons are considered the primary mechanism for mosaic plasmid formation, though other mechanisms have been observed in specific instances. The frequency with which mosaic plasmids have been described suggests they may play an important role in plasmid population dynamics. Our survey of the confirmed plasmid sequences available from complete and draft genomes in the RefSeq database shows that 46% of them fit a strict definition of mosaic. Mosaic plasmids are also not evenly distributed over the taxa represented in the database. Plasmids from some genera, including Piscirickettsia and Yersinia, are almost all mosaic, while plasmids from other genera, including Borrelia, are rarely mosaic. While some mosaic plasmids share identical regions with hundreds of others, the median mosaic plasmid only shares with 8 other plasmids. When considering only plasmids from finished genomes (51.6% of the total), mosaic plasmids have significantly higher proportions of transposase and antibiotic resistance genes. Conversely, only 56.6% of mosaic fragments (DNA fragments shared between mosaic plasmids) contain a recognizable transposase gene, and only 1.2% of mosaic fragments are flanked by inverted repeats. Mosaic fragments associated with the IS26 transposase gene are 3.8-fold more abundant than any other sequence shared between mosaic plasmids in the database, though this is at least partly due to overrepresentation of Enterobacteriaceae plasmids. Mosaic plasmids are a complicated trait of some plasmid populations, only partly explained by transposition. Though antibiotic resistance genes led to the identification of many mosaic plasmids, mosaic plasmids are a broad phenomenon encompassing many more traits than just antibiotic resistance. Further research will be required to determine the influence of ecology, host repair mechanisms, conjugation, and plasmid host range on the formation and influence of mosaic plasmids. AUTHOR SUMMARY: Plasmids are extrachromosomal genetic entities that are found in many prokaryotes. They serve as flexible storage for genes, and individual cells can make substantial changes to their characteristics by acquiring, losing, or modifying a plasmid. In some pathogenic bacteria, such as Escherichia coli, antibiotic resistance genes are known to spread primarily on plasmids. By analyzing a database of 8592 plasmid sequences we determined that many of these plasmids have exchanged genes with each other, becoming mosaics of genes from different sources. We next separated these plasmids into groups based on the organism they were isolated from and found that different groups had different fractions of mosaic plasmids. This result was unexpected and suggests that the mechanisms and selective pressures causing mosaic plasmids do not occur evenly over all species. It also suggests that plasmids may provide different levels of potential variation to different species. This work uncovers a previously unrecognized pattern in plasmids across prokaryotes, that could lead to new insights into the evolutionary role that plasmids play.

Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data.

The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitates initial use of empiric (frequently broad-spectrum) antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0 and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance factors and incomplete genome assembly confounded the rules-based algorithm, resulting in predictions based on gene family, rather than on knowledge of the specific variant found. Low-frequency resistance caused errors in the machine-learning algorithm because those genes were not seen or seen infrequently in the test set. We also identified an example of variability in the phenotype-based results that led to disagreement with both genotype-based methods. Genotype-based antimicrobial susceptibility testing shows great promise as a diagnostic tool, and we outline specific research goals to further refine this methodology.

Comparative transcriptomics elucidates adaptive phenol tolerance and utilization in lipid-accumulating Rhodococcus opacus PD630.

Lignin-derived (e.g. phenolic) compounds can compromise the bioconversion of lignocellulosic biomass to fuels and chemicals due to their toxicity and recalcitrance. The lipid-accumulating bacterium Rhodococcus opacus PD630 has recently emerged as a promising microbial host for lignocellulose conversion to value-added products due to its natural ability to tolerate and utilize phenolics. To gain a better understanding of its phenolic tolerance and utilization mechanisms, we adaptively evolved R. opacus over 40 passages using phenol as its sole carbon source (up to 373% growth improvement over wild-type), and extensively characterized two strains from passages 33 and 40. The two adapted strains showed higher phenol consumption rates (∼20 mg/l/h) and ∼2-fold higher lipid production from phenol than the wild-type strain. Whole-genome sequencing and comparative transcriptomics identified highly-upregulated degradation pathways and putative transporters for phenol in both adapted strains, highlighting the important linkage between mechanisms of regulated phenol uptake, utilization, and evolved tolerance. Our study shows that the R. opacus mutants are likely to use their transporters to import phenol rather than export them, suggesting a new aromatic tolerance mechanism. The identified tolerance genes and pathways are promising candidates for future metabolic engineering in R. opacus for improved lignin conversion to lipid-based products.

Synergistic, collaterally sensitive ß-lactam combinations suppress resistance in MRSA.

Methicillin-resistant Staphylococcus aureus (MRSA) is one of the most prevalent multidrug-resistant pathogens worldwide, exhibiting increasing resistance to the latest antibiotic therapies. Here we show that the triple ß-lactam combination meropenem-piperacillin-tazobactam (ME/PI/TZ) acts synergistically and is bactericidal against MRSA subspecies N315 and 72 other clinical MRSA isolates in vitro and clears MRSA N315 infection in a mouse model. ME/PI/TZ suppresses evolution of resistance in MRSA via reciprocal collateral sensitivity of its constituents. We demonstrate that these activities also extend to other carbapenem-penicillin-ß-lactamase inhibitor combinations. ME/PI/TZ circumvents the tight regulation of the mec and bla operons in MRSA, the basis for inducible resistance to ß-lactam antibiotics. Furthermore, ME/PI/TZ subverts the function of penicillin-binding protein-2a (PBP2a) via allostery, which we propose as the mechanism for both synergy and collateral sensitivity. Showing in vivo activity similar to that of linezolid, ME/PI/TZ demonstrates that combinations of older ß-lactam antibiotics could be effective against MRSA infections in humans.

KPC and NDM-1 genes in related Enterobacteriaceae strains and plasmids from Pakistan and the United States.

To characterize the genomic context of New Delhi metallo-ß-lactamase-1 (NDM-1) and Klebsiella pneumoniae carbapenemase (KPC), we sequenced 78 Enterobacteriaceae isolates from Pakistan and the United States encoding KPC, NDM-1, or no carbapenemase. High similarities of the results indicate rapid spread of carbapenem resistance between strains, including globally disseminated pathogens.

The yin and yang of bacterial resilience in the human gut microbiota.

The human gut is home to trillions of microbes that form a symbiotic relationship with the human host. During health, the intestinal microbiota provides many benefits to the host and is generally resistant to colonization by new species; however, disruption of this complex community can lead to pathogen invasion, inflammation, and disease. Restoration and maintenance of a healthy gut microbiota composition requires effective therapies to reduce and prevent colonization of harmful bacteria (pathogens) while simultaneously promoting growth of beneficial bacteria (probiotics). Here we review the mechanisms by which the host modulates the gut community composition during health and disease, and we discuss prospects for antibiotic and probiotic therapy for restoration of a healthy intestinal community following disruption.

Genome-wide characterization of the SloR metalloregulome in Streptococcus mutans.

Streptococcus mutans is the primary causative agent of human dental caries, a ubiquitous infectious disease for which effective treatment strategies remain elusive. We investigated a 25-kDa SloR metalloregulatory protein in this oral pathogen, along with its target genes that contribute to cariogenesis. Previous studies have demonstrated manganese- and SloR-dependent repression of the sloABCR metal ion transport operon in S. mutans. In the present study, we demonstrate that S. mutans coordinates this repression with that of certain virulence attributes. Specifically, we noted virulence gene repression in a manganese-containing medium when SloR binds to promoter-proximal sequence palindromes on the S. mutans chromosome. We applied a genome-wide approach to elucidate the sequences to which SloR binds and to reveal additional "class I" genes that are subject to SloR- and manganese-dependent repression. These analyses identified 204 S. mutans genes that are preceded by one or more conserved palindromic SloR recognition elements (SREs). We cross-referenced these genes with those that we had identified previously as SloR and/or manganese modulated in microarray and real-time quantitative reverse transcription-PCR (qRT-PCR) experiments. From this analysis, we identified a number of S. mutans virulence genes that are subject to transcriptional upregulation by SloR and noted that such "class II"-type regulation is dependent on direct SloR binding to promoter-distal SREs. These observations are consistent with a bifunctional role for the SloR metalloregulator and implicate it as a target for the development of therapies aimed at alleviating S. mutans-induced caries formation.

Dynamic regulation of CD24 and the invasive, CD44posCD24neg phenotype in breast cancer cell lines.

INTRODUCTION: The invasive, mesenchymal phenotype of CD44posCD24neg breast cancer cells has made them a promising target for eliminating the metastatic capacity of primary tumors. It has been previously demonstrated that CD44neg/lowCD24pos breast cancer cells lack the ability to give rise to their invasive CD44posCD24neg counterpart. Here we demonstrate that noninvasive, epithelial-like CD44posCD24pos cells readily give rise to invasive, mesenchymal CD44posCD24neg progeny in vivo and in vitro. This interconversion was found to be dependent upon Activin/Nodal signaling. METHODS: Breast cancer cell lines were sorted into CD44posCD24pos and CD44posCD24neg populations to evaluate their progeny for the expression of CD44, CD24, and markers of a mesenchymal phenotype. The populations, separated by fluorescence activated cell sorting (FACS) were injected into immunocompromised mice to evaluate their tumorigenicity and invasiveness of the resulting xenografts. RESULTS: CD24 expression was dynamically regulated in vitro in all evaluated breast cancer cell lines. Furthermore, a single noninvasive, epithelial-like CD44posCD24pos cell had the ability to give rise to invasive, mesenchymal CD44posCD24neg progeny. Importantly, this interconversion occurred in vivo as CD44posCD24pos cells gave rise to xenografts with locally invasive borders as seen in xenografts initiated with CD44posCD24neg cells. Lastly, the ability of CD44posCD24pos cells to give rise to mesenchymal progeny, and vice versa, was blocked upon ablation of Activin/Nodal signaling. CONCLUSIONS: Our data demonstrate that the invasive, mesenchymal CD44posCD24neg phenotype is under dynamic control in breast cancer cell lines both in vitro and in vivo. Furthermore, our observations suggest that therapies targeting CD44posCD24neg tumor cells may have limited success in preventing primary tumor metastasis unless Activin/Nodal signaling is arrested.