Analysis of the contribution of MTP and the predicted Flp pilus genes to Mycobacterium tuberculosis pathogenesis

Mycobacterium tuberculosis (Mtb) is one of the world's most successful pathogens. Millions of new cases of tuberculosis occur each year, emphasizing the need for better methods of treatment. The design of novel therapeutics is dependent on our understanding of factors that are essential for pathogenesis. Many bacterial pathogens use pili and other adhesins to mediate pathogenesis. The recently identified Mycobacterium tuberculosis pilus (MTP) and the hypothetical, widely conserved Flp pilus have been speculated to be important for Mtb virulence based on in vitro studies and homology to other pili, respectively. However, the roles for these pili during infection have yet to be tested. We addressed this gap in knowledge and found that neither MTP nor the hypothetical Flp pilus is required for Mtb survival in mouse models of infection, although MTP can contribute to biofilm formation and subsequent isoniazid tolerance. However, differences in mtp expression did affect lesion architecture in infected lungs. Deletion of mtp did not correlate with loss of cell-associated extracellular structures as visualized by transmission electron microscopy in Mtb Erdman and HN878 strains, suggesting that the phenotypes of the mtp mutants were not due to defects in production of extracellular structures. These findings highlight the importance of testing the virulence of adhesion mutants in animal models to assess the contribution of the adhesin to infection. This study also underscores the need for further investigation into additional strategies that Mtb may use to adhere to its host so that we may understand how this pathogen invades, colonizes and disseminates

Integrated Genomic and Social Network Analyses of Severe Acute Respiratory Syndrome Coronavirus 2 Transmission in the Healthcare Setting

BackgroundInfection prevention (IP) measures are designed to mitigate the transmission of pathogens in healthcare. Using large-scale viral genomic and social network analyses, we determined if IP measures used during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were adequate in protecting healthcare workers (HCWs) and patients from acquiring SARS-CoV-2.MethodsWe performed retrospective cross-sectional analyses of viral genomics from all available SARS-CoV-2 viral samples collected at UC San Diego Health and social network analysis using the electronic medical record to derive temporospatial overlap of infections among related viromes and supplemented with contact tracing data. The outcome measure was any instance of healthcare transmission, defined as cases with closely related viral genomes and epidemiological connection within the healthcare setting during the infection window. Between November 2020 through January 2022, 12 933 viral genomes were obtained from 35 666 patients and HCWs.ResultsAmong 5112 SARS-CoV-2 viral samples sequenced from the second and third waves of SARS-CoV-2 (pre-Omicron), 291 pairs were derived from persons with a plausible healthcare overlap. Of these, 34 pairs (12%) were phylogenetically linked: 19 attributable to household and 14 to healthcare transmission. During the Omicron wave, 2106 contact pairs among 7821 sequences resulted in 120 (6%) related pairs among 32 clusters, of which 10 were consistent with healthcare transmission. Transmission was more likely to occur in shared spaces in the older hospital compared with the newer hospital (2.54 vs 0.63 transmission events per 1000 admissions, P < .001).ConclusionsIP strategies were effective at identifying and preventing healthcare SARS-CoV-2 transmission

Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission.

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing and/or sequencing capacity, which can also introduce biases1-3. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing4,5. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission