Understanding the risks of co-exposures in a changing world: a case study of dual monitoring of the biotoxin domoic acid and Vibrio spp. in Pacific oyster.

Assessing the co-occurrence of multiple health risk factors in coastal ecosystems is challenging due to the complexity of multi-factor interactions and limited availability of simultaneously collected data. Understanding co-occurrence is particularly important for risk factors that may be associated with, or occur in similar environmental conditions. In marine ecosystems, the co-occurrence of harmful algal bloom toxins and bacterial pathogens within the genus Vibrio may impact both ecosystem and human health. This study examined the co-occurrence of Vibrio spp. and domoic acid (DA) produced by the harmful algae Pseudo-nitzschia by (1) analyzing existing California Department of Public Health monitoring data for V. parahaemolyticus and DA in oysters; and (2) conducting a 1-year seasonal monitoring of these risk factors across two Southern California embayments. Existing public health monitoring efforts in the state were robust for individual risk factors; however, it was difficult to evaluate the co-occurrence of these risk factors in oysters due to low number of co-monitoring instances between 2015 and 2020. Seasonal co-monitoring of DA and Vibrio spp. (V. vulnificus or V. parahaemolyticus) at two embayments revealed the co-occurrence of these health risk factors in 35% of sampled oysters in most seasons. Interestingly, both the overall detection frequency and co-occurrence of these risk factors were considerably less frequent in water samples. These findings may in part suggest the slow depuration of Vibrio spp. and DA in oysters as residual levels may be retained. This study expanded our understanding of the simultaneous presence of DA and Vibrio spp. in bivalves and demonstrates the feasibility of co-monitoring different risk factors from the same sample. Individual programs monitoring for different risk factors from the same sample matrix may consider combining efforts to reduce cost, streamline the process, and better understand the prevalence of co-occurring health risk factors.

Microbiome is not linked to clinical disease severity of familial Mediterranean fever in an international cohort of children.

OBJECTIVES: The severity of familial Mediterranean fever (FMF) may vary in different areas, suggesting a role for environmental factors. We analysed the composition of gut microbiota among children with FMF and healthy controls from Turkey and the USA and determined its effect on disease severity. METHODS: Children with FMF with pathogenic MEFV mutations and healthy controls from Turkey and the USA were enrolled. FMF disease activity was evaluated with the Autoinflammatory Disease Activity Index (AIDAI). Gut bacterial diversity was assessed by sequencing 16S rRNA gene libraries. RESULTS: We included 36 children from Turkey (28 patients with FMF, 8 healthy controls), and 21 patients and 6 controls from the USA. In the Turkish group, 28.6% of patients had severe disease, while 13.3% of US group patients had severe disease. As expected, we observed substantial differences between the gut microbiota of children from the two geographic regions, with Turkish patients and controls exhibiting higher relative abundances of Bacteriodia, while US patients and controls exhibited higher relative abundances of Clostridia. Alpha- and betadiversity did not differ significantly between FMF patients and controls, and neither was predictive of disease severity within each geographic region. We observed differences between FMF patients and controls in the relative abundance of some bacterial taxa at the amplicon sequence variant (ASV) level, but these differences received mixed statistical support. CONCLUSIONS: Among an international cohort of children with FMF, we did not find a strong effect of gut microbiota composition on disease severity. Other environmental or epigenetic factors may be operative.

SARS-CoV-2 detection status associates with bacterial community composition in patients and the hospital environment.

BACKGROUND: SARS-CoV-2 is an RNA virus responsible for the coronavirus disease 2019 (COVID-19) pandemic. Viruses exist in complex microbial environments, and recent studies have revealed both synergistic and antagonistic effects of specific bacterial taxa on viral prevalence and infectivity. We set out to test whether specific bacterial communities predict SARS-CoV-2 occurrence in a hospital setting. METHODS: We collected 972 samples from hospitalized patients with COVID-19, their health care providers, and hospital surfaces before, during, and after admission. We screened for SARS-CoV-2 using RT-qPCR, characterized microbial communities using 16S rRNA gene amplicon sequencing, and used these bacterial profiles to classify SARS-CoV-2 RNA detection with a random forest model. RESULTS: Sixteen percent of surfaces from COVID-19 patient rooms had detectable SARS-CoV-2 RNA, although infectivity was not assessed. The highest prevalence was in floor samples next to patient beds (39%) and directly outside their rooms (29%). Although bed rail samples more closely resembled the patient microbiome compared to floor samples, SARS-CoV-2 RNA was detected less often in bed rail samples (11%). SARS-CoV-2 positive samples had higher bacterial phylogenetic diversity in both human and surface samples and higher biomass in floor samples. 16S microbial community profiles enabled high classifier accuracy for SARS-CoV-2 status in not only nares, but also forehead, stool, and floor samples. Across these distinct microbial profiles, a single amplicon sequence variant from the genus Rothia strongly predicted SARS-CoV-2 presence across sample types, with greater prevalence in positive surface and human samples, even when compared to samples from patients in other intensive care units prior to the COVID-19 pandemic. CONCLUSIONS: These results contextualize the vast diversity of microbial niches where SARS-CoV-2 RNA is detected and identify specific bacterial taxa that associate with the viral RNA prevalence both in the host and hospital environment. Video Abstract.

Detecting personal microbiota signatures at artificial crime scenes.

When mapped to the environments we interact with on a daily basis, the 36 million microbial cells per hour that humans emit leave a trail of evidence that can be leveraged for forensic analysis. We employed 16S rRNA amplicon sequencing to map unique microbial sequence variants between human skin and building surfaces in three experimental conditions: over time during controlled and uncontrolled incidental interactions with a door handle, and during multiple mock burglaries in ten real residences. We demonstrate that humans (n = 30) leave behind microbial signatures that can be used to track interaction with various surfaces within a building, but the likelihood of accurately detecting the specific burglar for a given home was between 20-25%. Also, the human microbiome contains rare microbial taxa that can be combined to create a unique microbial profile, which when compared to 600 other individuals can improve our ability to link an individual 'burglar' to a residence. In total, 5512 discriminating, non-singleton unique exact sequence variants (uESVs) were identified as unique to an individual, with a minimum of 1 and a maximum of 568, suggesting some people maintain a greater degree of unique taxa compared to our population of 600. Approximate 60-77% of the unique exact sequence variants originated from the hands of participants, and these microbial discriminators spanned 36 phyla but were dominated by the Proteobacteria (34%). A fitted regression generated to determine whether an intruder's uESVs found on door handles in an office decayed over time in the presence or absence of office workers, found no significant shift in proportion of uESVs over time irrespective of the presence of office workers. While it was possible to detect the correct burglars' microbiota as having contributed to the invaded space, the predictions were very weak in comparison to accepted forensic standards. This suggests that at this time 16S rRNA amplicon sequencing of the built environment microbiota cannot be used as a reliable trace evidence standard for criminal investigations.

Dysbiosis in Children Born by Caesarean Section.

The rate of Caesarean-section delivery in the United States has increased by 60% from 1996 through to 2013 and now accounts for > 30% of births [CDC, 2017]. The purpose of this review is to present the current understanding of both the microbial risk factors that increase the likelihood of a Caesarean-section delivery and the microbial dysbiosis that is thought to result from the Caesarean section. We provide examples of research into the impact of early-life microbial dysbiosis on infant development and long-term health outcomes, as well as consider the efficacy and the long-term implications of microbiome-based therapies to mitigate this dysbiosis. The steep rise in the Caesarean-section delivery rate makes it imperative to understand the potential of microbiota modulation for the treatment of dysbiosis.