Tracking gut microbiome and bloodstream infection in critically ill adults.

BackgroundThe gut microbiome is believed to contribute to bloodstream infection (BSI) via translocation of dominant gut bacteria in vulnerable patient populations. However, conclusively linking gut and blood organisms requires stringent approaches to establish strain-level identity.MethodsWe enrolled a convenience cohort of critically ill patients and investigated 86 bloodstream infection episodes that occurred in 57 patients. Shotgun metagenomic sequencing was used to define constituents of their gut microbiomes, and whole genome sequencing and assembly was done on 23 unique bloodstream isolates that were available from 21 patients. Whole genome sequences were downloaded from public databases and used to establish sequence-identity distribution and define thresholds for unrelated genomes of BSI species. Gut microbiome reads were then aligned to whole genome sequences of the cognate bloodstream isolate and unrelated database isolates to assess identity.ResultsGut microbiome constituents matching the bloodstream infection species were present in half of BSI episodes, and represented >30% relative abundance of gut sequences in 10% of episodes. Among the 23 unique bloodstream organisms that were available for whole genome sequencing, 14 were present in gut at the species level. Sequence alignment applying defined thresholds for identity revealed that 6 met criteria for identical strains in blood and gut, but 8 did not. Sequence identity between BSI isolates and gut microbiome reads was more likely when the species was present at higher relative abundance in gut.ConclusionIn assessing potential gut source for BSI, stringent sequence-based approaches are essential to determine if organisms responsible for BSI are identical to those in gut: of 14 evaluable patients in which the same species was present in both sites, they were identical in 6/14, but were non-identical in 8/14 and thus inconsistent with gut source. This report demonstrates application of sequencing as a key tool to investigate infection tracking within patients

SARS-CoV-2 evolution during prolonged infection in immunocompromised patients

ABSTRACTProlonged infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in immunocompromised patients provides an opportunity for viral evolution, potentially leading to the generation of new pathogenic variants. To investigate the pathways of viral evolution, we carried out a study on five patients experiencing prolonged SARS-CoV-2 infection (quantitative polymerase chain reaction-positive for 79–203 days) who were immunocompromised due to treatment for lymphoma or solid organ transplantation. For each timepoint analyzed, we generated at least two independent viral genome sequences to assess the heterogeneity and control for sequencing error. Four of the five patients likely had prolonged infection; the fifth apparently experienced a reinfection. The rates of accumulation of substitutions in the viral genome per day were higher in hospitalized patients with prolonged infection than those estimated for the community background. The spike coding region accumulated a significantly greater number of unique mutations than other viral coding regions, and the mutation density was higher. Two patients were treated with monoclonal antibodies (bebtelovimab and sotrovimab); by the next sampled timepoint, each virus population showed substitutions associated with monoclonal antibody resistance as the dominant forms (spike K444N and spike E340D). All patients received remdesivir, but remdesivir-resistant substitutions were not detected. These data thus help elucidate the trends of emergence, evolution, and selection of mutational variants within long-term infected immunocompromised individuals.IMPORTANCESARS-CoV-2 is responsible for a global pandemic, driven in part by the emergence of new viral variants. Where do these new variants come from? One model is that long-term viral persistence in infected individuals allows for viral evolution in response to host pressures, resulting in viruses more likely to replicate efficiently in humans. In this study, we characterize replication in several hospitalized and long-term infected individuals, documenting efficient pathways of viral evolution

Association between detection of BSI species in the gut microbiome and selected underlying conditions.

Association between detection of BSI species in the gut microbiome and selected underlying conditions.</p

Metagenomic stool samples analyzed.

BackgroundThe gut microbiome is believed to contribute to bloodstream infection (BSI) via translocation of dominant gut bacteria in vulnerable patient populations. However, conclusively linking gut and blood organisms requires stringent approaches to establish strain-level identity.MethodsWe enrolled a convenience cohort of critically ill patients and investigated 86 bloodstream infection episodes that occurred in 57 patients. Shotgun metagenomic sequencing was used to define constituents of their gut microbiomes, and whole genome sequencing and assembly was done on 23 unique bloodstream isolates that were available from 21 patients. Whole genome sequences were downloaded from public databases and used to establish sequence-identity distribution and define thresholds for unrelated genomes of BSI species. Gut microbiome reads were then aligned to whole genome sequences of the cognate bloodstream isolate and unrelated database isolates to assess identity.ResultsGut microbiome constituents matching the bloodstream infection species were present in half of BSI episodes, and represented >30% relative abundance of gut sequences in 10% of episodes. Among the 23 unique bloodstream organisms that were available for whole genome sequencing, 14 were present in gut at the species level. Sequence alignment applying defined thresholds for identity revealed that 6 met criteria for identical strains in blood and gut, but 8 did not. Sequence identity between BSI isolates and gut microbiome reads was more likely when the species was present at higher relative abundance in gut.ConclusionIn assessing potential gut source for BSI, stringent sequence-based approaches are essential to determine if organisms responsible for BSI are identical to those in gut: of 14 evaluable patients in which the same species was present in both sites, they were identical in 6/14, but were non-identical in 8/14 and thus inconsistent with gut source. This report demonstrates application of sequencing as a key tool to investigate infection tracking within patients.</div

Schematic of gut microbiome and BSI whole genome sequence (WGS) analysis.

BSI isolates (A) and stool (B) were subjected to shotgun metagenomic deep sequencing. Stool samples were used for microbiome analysis of composition, diversity and dominance (C). BSI isolates were used for assembly of whole genomes (D). Stool and BSI WGS together were used to test identity between organisms in the stool and blood culture isolates by mapping stool reads to the cognate BSI WGS (E). Single nucleotide variants per mega base pair (SNV/Mbp) was calculated to represent the degree of mismatch, and WGS of BSI isolates of same species from the cohort (if available) and reference genomes downloaded from databases were included as control comparisons (hypothetical example shown in F).</p

Gut microbiota of critically ill patients are dysbiotic but do not differ among those with or without bloodstream infection.

Stool samples all critically ill subjects enrolled in the study were compared with healthy individuals reported from the Human Microbiome Project (HMP). (A) Bar graph representing phylum level composition of critically ill and healthy subjects clustered by Bray-Curtis dissimilarity. Some critically ill subjects’ gut microbiota resembles the gut microbiome composition of healthy individuals, while others are dysbiotic and dominated by Proteobacteria, Firmicutes, or fungi (Ascomycota). (B) Alpha diversity using the Shannon index. Critically ill subjects are colored based on whether they did (BSI+; green) or did not (BSI-; red) have a bloodstream infection. Healthy and critically ill are significantly different (p = 0.003; Wilcoxon rank-sum with Benjamini-Hochberg adjustment for false discovery) but there is no difference between critically ill/BSI + and critically ill/BSI- groups. (C) Dominance by the Berger-Parker dominance index. Healthy and critically ill are significantly different (p = 0.008; Wilcoxon rank-sum with Benjamini-Hochberg adjustment for false discovery), but there is no difference between critically ill/BSI+ and critically ill/BSI- groups. (D) Principal coordinate analysis of stool microbiota based on Bray-Curtis dissimilarity. Critically ill subjects diverge significantly from healthy individuals (PERMANOVA with Benjamini-Hochberg adjustment for false discovery; p = 0.008) but critically ill/BSI+ and critically ill/BSI- do not differ from each other from each other. Panel A includes all stool samples, while panels B-D include just the first collected sample for each subject.</p

Reference genomes used for pangenome analysis.

BackgroundThe gut microbiome is believed to contribute to bloodstream infection (BSI) via translocation of dominant gut bacteria in vulnerable patient populations. However, conclusively linking gut and blood organisms requires stringent approaches to establish strain-level identity.MethodsWe enrolled a convenience cohort of critically ill patients and investigated 86 bloodstream infection episodes that occurred in 57 patients. Shotgun metagenomic sequencing was used to define constituents of their gut microbiomes, and whole genome sequencing and assembly was done on 23 unique bloodstream isolates that were available from 21 patients. Whole genome sequences were downloaded from public databases and used to establish sequence-identity distribution and define thresholds for unrelated genomes of BSI species. Gut microbiome reads were then aligned to whole genome sequences of the cognate bloodstream isolate and unrelated database isolates to assess identity.ResultsGut microbiome constituents matching the bloodstream infection species were present in half of BSI episodes, and represented >30% relative abundance of gut sequences in 10% of episodes. Among the 23 unique bloodstream organisms that were available for whole genome sequencing, 14 were present in gut at the species level. Sequence alignment applying defined thresholds for identity revealed that 6 met criteria for identical strains in blood and gut, but 8 did not. Sequence identity between BSI isolates and gut microbiome reads was more likely when the species was present at higher relative abundance in gut.ConclusionIn assessing potential gut source for BSI, stringent sequence-based approaches are essential to determine if organisms responsible for BSI are identical to those in gut: of 14 evaluable patients in which the same species was present in both sites, they were identical in 6/14, but were non-identical in 8/14 and thus inconsistent with gut source. This report demonstrates application of sequencing as a key tool to investigate infection tracking within patients.</div

Clinical characteristics of enrolled patients.

Major diagnosis refers to most common principal acute and underlying reasons for ICU stay; full details are in S1 Table. Numbers add to greater than 100% due to concomitant processes. There are no significant differences in any clinical characteristics between BSI-positive subjects and BSI-negative subjects or between BSI-positive subjects and BC-available subjects (chi-square test if categorical, t-test if continuous; applying 0.05 significance threshold).</p

BSI episodes where species were detected in gut.

Subjects are ordered by the relative abundance of BSI species in highest abundance stool sample, and grouped into those with dominant (≥30%), 2.5–30%, and 0.1–2.5% relative abundances. The last column indicates whether the stool reads matched the BSI isolate WGS for those episodes where the BSI isolate was available for sequencing.</p