Microbial-enrichment method enables high-throughput metagenomic characterization from host-rich samples.

Host-microbe interactions have been linked to health and disease states through the use of microbial taxonomic profiling, mostly via 16S ribosomal RNA gene sequencing. However, many mechanistic insights remain elusive, in part because studying the genomes of microbes associated with mammalian tissue is difficult due to the high ratio of host to microbial DNA in such samples. Here we describe a microbial-enrichment method (MEM), which we demonstrate on a wide range of sample types, including saliva, stool, intestinal scrapings, and intestinal mucosal biopsies. MEM enabled high-throughput characterization of microbial metagenomes from human intestinal biopsies by reducing host DNA more than 1,000-fold with minimal microbial community changes (roughly 90% of taxa had no significant differences between MEM-treated and untreated control groups). Shotgun sequencing of MEM-treated human intestinal biopsies enabled characterization of both high- and low-abundance microbial taxa, pathways and genes longitudinally along the gastrointestinal tract. We report the construction of metagenome-assembled genomes directly from human intestinal biopsies for bacteria and archaea at relative abundances as low as 1%. Analysis of metagenome-assembled genomes reveals distinct subpopulation structures between the small and large intestine for some taxa. MEM opens a path for the microbiome field to acquire deeper insights into host-microbe interactions by enabling in-depth characterization of host-tissue-associated microbial communities.

GATA4 controls regionalization of tissue immunity and commensal-driven immunopathology.

There is growing recognition that regionalization of bacterial colonization and immunity along the intestinal tract has an important role in health and disease. Yet, the mechanisms underlying intestinal regionalization and its dysregulation in disease are not well understood. This study found that regional epithelial expression of the transcription factor GATA4 controls bacterial colonization and inflammatory tissue immunity in the proximal small intestine by regulating retinol metabolism and luminal IgA. Furthermore, in mice without jejunal GATA4 expression, the commensal segmented filamentous bacteria promoted pathogenic inflammatory immune responses that disrupted barrier function and increased mortality upon Citrobacter rodentium infection. In celiac disease patients, low GATA4 expression was associated with metabolic alterations, mucosal Actinobacillus, and increased IL-17 immunity. Taken together, these results reveal broad impacts of GATA4-regulated intestinal regionalization on bacterial colonization and tissue immunity, highlighting an elaborate interdependence of intestinal metabolism, immunity, and microbiota in homeostasis and disease.

Morning SARS-CoV-2 Testing Yields Better Detection of Infection Due to Higher Viral Loads in Saliva and Nasal Swabs upon Waking.

Optimizing specimen collection methods to achieve the most reliable SARS-CoV-2 detection for a given diagnostic sensitivity would improve testing and minimize COVID-19 outbreaks. From September 2020 to April 2021, we performed a household-transmission study in which participants self-collected specimens every morning and evening throughout acute SARS-CoV-2 infection. Seventy mildly symptomatic participants collected saliva, and of those, 29 also collected nasal swab specimens. Viral load was quantified in 1,194 saliva and 661 nasal swab specimens using a high-analytical-sensitivity reverse transcription-quantitative PCR (RT-qPCR) assay. Viral loads in both saliva and nasal swab specimens were significantly higher in morning-collected specimens than in evening-collected specimens after symptom onset. This aspect of the biology of SARS-CoV-2 infection has implications for diagnostic testing. We infer that morning collection would have resulted in significantly improved detection and that this advantage would be most pronounced for tests with low to moderate analytical sensitivity. Collecting specimens for COVID-19 testing in the morning offers a simple and low-cost improvement to clinical diagnostic sensitivity of low- to moderate-analytical-sensitivity tests. IMPORTANCE Our findings suggest that collecting saliva and nasal swab specimens in the morning immediately after waking yields higher SARS-CoV-2 viral loads than collection later in the day. The higher viral loads from morning specimen collection are predicted to significantly improve detection of SARS-CoV-2 in symptomatic individuals, particularly when using moderate- to low-analytical-sensitivity COVID-19 diagnostic tests, such as rapid antigen tests.

Quantitative SARS-CoV-2 Viral-Load Curves in Paired Saliva Samples and Nasal Swabs Inform Appropriate Respiratory Sampling Site and Analytical Test Sensitivity Required for Earliest Viral Detection.

Early detection of SARS-CoV-2 infection is critical to reduce asymptomatic and presymptomatic transmission, curb the spread of variants, and maximize treatment efficacy. Low-analytical-sensitivity nasal-swab testing is commonly used for surveillance and symptomatic testing, but the ability of these tests to detect the earliest stages of infection has not been established. In this study, conducted between September 2020 and June 2021 in the greater Los Angeles County, California, area, initially SARS-CoV-2-negative household contacts of individuals diagnosed with COVID-19 prospectively self-collected paired anterior-nares nasal-swab and saliva samples twice daily for viral-load quantification by high-sensitivity reverse-transcription quantitative PCR (RT-qPCR) and digital-RT-PCR assays. We captured viral-load profiles from the incidence of infection for seven individuals and compared diagnostic sensitivities between respiratory sites. Among unvaccinated persons, testing saliva with a high-analytical-sensitivity assay detected infection up to 4.5 days before viral loads in nasal swabs reached concentrations detectable by low-analytical-sensitivity nasal-swab tests. For most participants, nasal swabs reached higher peak viral loads than saliva but were undetectable or at lower loads during the first few days of infection. High-analytical-sensitivity saliva testing was most reliable for earliest detection. Our study illustrates the value of acquiring early (within hours after a negative high-sensitivity test) viral-load profiles to guide the appropriate analytical sensitivity and respiratory site for detecting earliest infections. Such data are challenging to acquire but critical to designing optimal testing strategies with emerging variants in the current pandemic and to respond to future viral pandemics.

Quantitative sequencing clarifies the role of disruptor taxa, oral microbiota, and strict anaerobes in the human small-intestine microbiome.

BACKGROUND: Upper gastrointestinal (GI) disorders and abdominal pain afflict between 12 and 30% of the worldwide population and research suggests these conditions are linked to the gut microbiome. Although large-intestine microbiota have been linked to several GI diseases, the microbiota of the human small intestine and its relation to human disease has been understudied. The small intestine is the major site for immune surveillance in the gut, and compared with the large intestine, it has greater than 100 times the surface area and a thinner and more permeable mucus layer. RESULTS: Using quantitative sequencing, we evaluated total and taxon-specific absolute microbial loads from 250 duodenal-aspirate samples and 21 paired duodenum-saliva samples from participants in the REIMAGINE study. Log-transformed total microbial loads spanned 5 logs and were normally distributed. Paired saliva-duodenum samples suggested potential transmission of oral microbes to the duodenum, including organisms from the HACEK group. Several taxa, including Klebsiella, Escherichia, Enterococcus, and Clostridium, seemed to displace strict anaerobes common in the duodenum, so we refer to these taxa as disruptors. Disruptor taxa were enriched in samples with high total microbial loads and in individuals with small intestinal bacterial overgrowth (SIBO). Absolute loads of disruptors were associated with more severe GI symptoms, highlighting the value of absolute taxon quantification when studying small-intestine health and function. CONCLUSION: This study provides the largest dataset of the absolute abundance of microbiota from the human duodenum to date. The results reveal a clear relationship between the oral microbiota and the duodenal microbiota and suggest an association between the absolute abundance of disruptor taxa, SIBO, and the prevalence of severe GI symptoms. Video Abstract.

Alterations in the gut microbiota contribute to cognitive impairment induced by the ketogenic diet and hypoxia.

Many genetic and environmental factors increase susceptibility to cognitive impairment (CI), and the gut microbiome is increasingly implicated. However, the identity of gut microbes associated with CI risk, their effects on CI, and their mechanisms remain unclear. Here, we show that a carbohydrate-restricted (ketogenic) diet potentiates CI induced by intermittent hypoxia in mice and alters the gut microbiota. Depleting the microbiome reduces CI, whereas transplantation of the risk-associated microbiome or monocolonization with Bilophila wadsworthia confers CI in mice fed a standard diet. B. wadsworthia and the risk-associated microbiome disrupt hippocampal synaptic plasticity, neurogenesis, and gene expression. The CI is associated with microbiome-dependent increases in intestinal interferon-gamma (IFNg)-producing Th1 cells. Inhibiting Th1 cell development abrogates the adverse effects of both B. wadsworthia and environmental risk factors on CI. Together, these findings identify select gut bacteria that contribute to environmental risk for CI in mice by promoting inflammation and hippocampal dysfunction.

Microbiota regulate social behaviour via stress response neurons in the brain.

Social interactions among animals mediate essential behaviours, including mating, nurturing, and defence1,2. The gut microbiota contribute to social activity in mice3,4, but the gut-brain connections that regulate this complex behaviour and its underlying neural basis are unclear5,6. Here we show that the microbiome modulates neuronal activity in specific brain regions of male mice to regulate canonical stress responses and social behaviours. Social deviation in germ-free and antibiotic-treated mice is associated with elevated levels of the stress hormone corticosterone, which is primarily produced by activation of the hypothalamus-pituitary-adrenal (HPA) axis. Adrenalectomy, antagonism of glucocorticoid receptors, or pharmacological inhibition of corticosterone synthesis effectively corrects social deficits following microbiome depletion. Genetic ablation of glucocorticoid receptors in specific brain regions or chemogenetic inactivation of neurons in the paraventricular nucleus of the hypothalamus that produce corticotrophin-releasing hormone (CRH) reverse social impairments in antibiotic-treated mice. Conversely, specific activation of CRH-expressing neurons in the paraventricular nucleus induces social deficits in mice with a normal microbiome. Via microbiome profiling and in vivo selection, we identify a bacterial species, Enterococcus faecalis, that promotes social activity and reduces corticosterone levels in mice following social stress. These studies suggest that specific gut bacteria can restrain the activation of the HPA axis, and show that the microbiome can affect social behaviours through discrete neuronal circuits that mediate stress responses in the brain.

Quantitative SARS-CoV-2 viral-load curves in paired saliva and nasal swabs inform appropriate respiratory sampling site and analytical test sensitivity required for earliest viral detection.

Early detection of SARS-CoV-2 infection is critical to reduce asymptomatic and pre-symptomatic transmission, curb the spread of variants by travelers, and maximize treatment efficacy. Low-sensitivity nasal-swab testing (antigen and some nucleic-acid-amplification tests) is commonly used for surveillance and symptomatic testing, but the ability of low-sensitivity nasal-swab tests to detect the earliest stages of infection has not been established. In this case-ascertained study, initially-SARS-CoV-2-negative household contacts of individuals diagnosed with COVID-19 prospectively self-collected paired anterior-nares nasal-swab and saliva samples twice daily for viral-load quantification by high-sensitivity RT-qPCR and digital-RT-PCR assays. We captured viral-load profiles from the incidence of infection for seven individuals and compared diagnostic sensitivities between respiratory sites. Among unvaccinated persons, high-sensitivity saliva testing detected infection up to 4.5 days before viral loads in nasal swabs reached the limit of detection of low-sensitivity nasal-swab tests. For most participants, nasal swabs reached higher peak viral loads than saliva, but were undetectable or at lower loads during the first few days of infection. High-sensitivity saliva testing was most reliable for earliest detection. Our study illustrates the value of acquiring early (within hours after a negative high-sensitivity test) viral-load profiles to guide the appropriate analytical sensitivity and respiratory site for detecting earliest infections. Such data are challenging to acquire but critical to design optimal testing strategies in the current pandemic and will be required for responding to future viral pandemics. As new variants and viruses emerge, up-to-date data on viral kinetics are necessary to adjust testing strategies for reliable early detection of infections.

SARS-CoV-2 Viral Load in Saliva Rises Gradually and to Moderate Levels in Some Humans.

Transmission of SARS-CoV-2 in community settings often occurs before symptom onset, therefore testing strategies that can reliably detect people in the early phase of infection are urgently needed. Early detection of SARS-CoV-2 infection is especially critical to protect vulnerable populations who require frequent interactions with caretakers. Rapid COVID-19 tests have been proposed as an attractive strategy for surveillance, however a limitation of most rapid tests is their low sensitivity. Low-sensitivity tests are comparable to high sensitivity tests in detecting early infections when two assumptions are met: (1) viral load rises quickly (within hours) after infection and (2) viral load reaches and sustains high levels (>105-106 RNA copies/mL). However, there are no human data testing these assumptions. In this study, we document a case of presymptomatic household transmission from a healthy young adult to a sibling and a parent. Participants prospectively provided twice-daily saliva samples. Samples were analyzed by RT-qPCR and RT-ddPCR and we measured the complete viral load profiles throughout the course of infection of the sibling and parent. This study provides evidence that in at least some human cases of SARS-CoV-2, viral load rises slowly (over days, not hours) and not to such high levels to be detectable reliably by any low-sensitivity test. Additional viral load profiles from different samples types across a broad demographic must be obtained to describe the early phase of infection and determine which testing strategies will be most effective for identifying SARS-CoV-2 infection before transmission can occur.

Publisher Correction: A quantitative sequencing framework for absolute abundance measurements of mucosal and lumenal microbial communities.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A quantitative sequencing framework for absolute abundance measurements of mucosal and lumenal microbial communities.

A fundamental goal in microbiome studies is determining which microbes affect host physiology. Standard methods for determining changes in microbial taxa measure relative, rather than absolute abundances. Moreover, studies often analyze only stool, despite microbial diversity differing substantially among gastrointestinal (GI) locations. Here, we develop a quantitative framework to measure absolute abundances of individual bacterial taxa by combining the precision of digital PCR with the high-throughput nature of 16S rRNA gene amplicon sequencing. In a murine ketogenic-diet study, we compare microbial loads in lumenal and mucosal samples along the GI tract. Quantitative measurements of absolute (but not relative) abundances reveal decreases in total microbial loads on the ketogenic diet and enable us to determine the differential effects of diet on each taxon in stool and small-intestine mucosa samples. This rigorous quantitative microbial analysis framework, appropriate for diverse GI locations enables mapping microbial biogeography of the mammalian GI tract and more accurate analyses of changes in microbial taxa in microbiome studies.

Real-time kinetics and high-resolution melt curves in single-molecule digital LAMP to differentiate and study specific and non-specific amplification.

Isothermal amplification assays, such as loop-mediated isothermal amplification (LAMP), show great utility for the development of rapid diagnostics for infectious diseases because they have high sensitivity, pathogen-specificity and potential for implementation at the point of care. However, elimination of non-specific amplification remains a key challenge for the optimization of LAMP assays. Here, using chlamydia DNA as a clinically relevant target and high-throughput sequencing as an analytical tool, we investigate a potential mechanism of non-specific amplification. We then develop a real-time digital LAMP (dLAMP) with high-resolution melting temperature (HRM) analysis and use this single-molecule approach to analyze approximately 1.2 million amplification events. We show that single-molecule HRM provides insight into specific and non-specific amplification in LAMP that are difficult to deduce from bulk measurements. We use real-time dLAMP with HRM to evaluate differences between polymerase enzymes, the impact of assay parameters (e.g. time, rate or florescence intensity), and the effect background human DNA. By differentiating true and false positives, HRM enables determination of the optimal assay and analysis parameters that leads to the lowest limit of detection (LOD) in a digital isothermal amplification assay.

RNA markers enable phenotypic test of antibiotic susceptibility in Neisseria gonorrhoeae after 10 minutes of ciprofloxacin exposure.

Antimicrobial-resistant Neisseria gonorrhoeae is an urgent public-health threat, with continued worldwide incidents of infection and rising resistance to antimicrobials. Traditional culture-based methods for antibiotic susceptibility testing are unacceptably slow (1-2 days), resulting in the use of broad-spectrum antibiotics and the further development and spread of resistance. Critically needed is a rapid antibiotic susceptibility test (AST) that can guide treatment at the point-of-care. Rapid phenotypic approaches using quantification of DNA have been demonstrated for fast-growing organisms (e.g. E. coli) but are challenging for slower-growing pathogens such as N. gonorrhoeae. Here, we investigate the potential of RNA signatures to provide phenotypic responses to antibiotics in N. gonorrhoeae that are faster and greater in magnitude compared with DNA. Using RNA sequencing, we identified antibiotic-responsive transcripts. Significant shifts (>4-fold change) in transcript levels occurred within 5 min of antibiotic exposure. We designed assays for responsive transcripts with the highest abundances and fold changes, and validated gene expression using digital PCR. Using the top two markers (porB and rpmB) we correctly determined the antibiotic susceptibility and resistance of 49 clinical isolates after 10 min exposure to ciprofloxacin. RNA signatures are therefore promising as an approach on which to build rapid AST devices for N. gonorrhoeae at the point-of-care, which is critical for disease management, surveillance, and antibiotic stewardship efforts.