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  • 1
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    Human Skin, Oral, and Gut Microbiomes Predict Chronological Age
    American Society for Microbiology ; 2020
    In:  mSystems Vol. 5, No. 1 ( 2020-02-11)
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    In: mSystems, American Society for Microbiology, Vol. 5, No. 1 ( 2020-02-11)
    Abstract: Human gut microbiomes are known to change with age, yet the relative value of human microbiomes across the body as predictors of age, and prediction robustness across populations is unknown. In this study, we tested the ability of the oral, gut, and skin (hand and forehead) microbiomes to predict age in adults using random forest regression on data combined from multiple publicly available studies, evaluating the models in each cohort individually. Intriguingly, the skin microbiome provides the best prediction of age (mean ± standard deviation, 3.8 ± 0.45 years, versus 4.5 ± 0.14 years for the oral microbiome and 11.5 ± 0.12 years for the gut microbiome). This also agrees with forensic studies showing that the skin microbiome predicts postmortem interval better than microbiomes from other body sites. Age prediction models constructed from the hand microbiome generalized to the forehead and vice versa, across cohorts, and results from the gut microbiome generalized across multiple cohorts (United States, United Kingdom, and China). Interestingly, taxa enriched in young individuals (18 to 30 years) tend to be more abundant and more prevalent than taxa enriched in elderly individuals ( 〉 60 yrs), suggesting a model in which physiological aging occurs concomitantly with the loss of key taxa over a lifetime, enabling potential microbiome-targeted therapeutic strategies to prevent aging. IMPORTANCE Considerable evidence suggests that the gut microbiome changes with age or even accelerates aging in adults. Whether the age-related changes in the gut microbiome are more or less prominent than those for other body sites and whether predictions can be made about a person’s age from a microbiome sample remain unknown. We therefore combined several large studies from different countries to determine which body site’s microbiome could most accurately predict age. We found that the skin was the best, on average yielding predictions within 4 years of chronological age. This study sets the stage for future research on the role of the microbiome in accelerating or decelerating the aging process and in the susceptibility for age-related diseases.
    Type of Medium: Online Resource
    ISSN: 2379-5077
    URL: Article
    DOI: 10.1128/mSystems.00630-19
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2020
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  • 2
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    Phylogeny-Aware Analysis of Metagenome Community Ecology Based on Matched Reference Genomes while Bypassing Taxonomy
    American Society for Microbiology ; 2022
    In:  mSystems Vol. 7, No. 2 ( 2022-04-26)
    Details
    In: mSystems, American Society for Microbiology, Vol. 7, No. 2 ( 2022-04-26)
    Abstract: We introduce the operational genomic unit (OGU) method, a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent of taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance, and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldom applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome data sets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project data set and more accurate prediction of human age by the gut microbiomes of Finnish individuals included in the FINRISK 2002 cohort. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate adoption of the OGU method in future metagenomics studies. IMPORTANCE Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. Current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution. To solve these challenges, we introduce operational genomic units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition and (ii) permitting use of phylogeny-aware tools. Our analysis of real-world data sets shows that it is advantageous over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGUs as an effective practice in metagenomic studies.
    Type of Medium: Online Resource
    ISSN: 2379-5077
    URL: Article
    DOI: 10.1128/msystems.00167-22
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2022
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  • 3
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    High-Throughput Wastewater SARS-CoV-2 Detection Enables Forecasting of Community Infection Dynamics in San Diego County
    American Society for Microbiology ; 2021
    In:  mSystems Vol. 6, No. 2 ( 2021-04-27)
    Details
    In: mSystems, American Society for Microbiology, Vol. 6, No. 2 ( 2021-04-27)
    Abstract: Large-scale wastewater surveillance has the ability to greatly augment the tracking of infection dynamics especially in communities where the prevalence rates far exceed the testing capacity. However, current methods for viral detection in wastewater are severely lacking in terms of scaling up for high throughput. In the present study, we employed an automated magnetic-bead-based concentration approach for viral detection in sewage that can effectively be scaled up for processing 24 samples in a single 40-min run. The method compared favorably to conventionally used methods for viral wastewater concentrations with higher recovery efficiencies from input sample volumes as low as 10 ml and can enable the processing of over 100 wastewater samples in a day. The sensitivity of the high-throughput protocol was shown to detect 1 asymptomatic individual in a building of 415 residents. Using the high-throughput pipeline, samples from the influent stream of the primary wastewater treatment plant of San Diego County (serving 2.3 million residents) were processed for a period of 13 weeks. Wastewater estimates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral genome copies in raw untreated wastewater correlated strongly with clinically reported cases by the county, and when used alongside past reported case numbers and temporal information in an autoregressive integrated moving average (ARIMA) model enabled prediction of new reported cases up to 3 weeks in advance. Taken together, the results show that the high-throughput surveillance could greatly ameliorate comprehensive community prevalence assessments by providing robust, rapid estimates. IMPORTANCE Wastewater monitoring has a lot of potential for revealing coronavirus disease 2019 (COVID-19) outbreaks before they happen because the virus is found in the wastewater before people have clinical symptoms. However, application of wastewater-based surveillance has been limited by long processing times specifically at the concentration step. Here we introduce a much faster method of processing the samples and show its robustness by demonstrating direct comparisons with existing methods and showing that we can predict cases in San Diego by a week with excellent accuracy, and 3 weeks with fair accuracy, using city sewage. The automated viral concentration method will greatly alleviate the major bottleneck in wastewater processing by reducing the turnaround time during epidemics.
    Type of Medium: Online Resource
    ISSN: 2379-5077
    URL: Article
    DOI: 10.1128/mSystems.00045-21
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2021
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  • 4
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    Implementation of Practical Surface SARS-CoV-2 Surveillance in School Settings
    American Society for Microbiology ; 2022
    In:  mSystems Vol. 7, No. 4 ( 2022-08-30)
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    In: mSystems, American Society for Microbiology, Vol. 7, No. 4 ( 2022-08-30)
    Abstract: Surface sampling for SARS-CoV-2 RNA detection has shown considerable promise to detect exposure of built environments to infected individuals shedding virus who would not otherwise be detected. Here, we compare two popular sampling media (VTM and SDS) and two popular workflows (Thermo and PerkinElmer) for implementation of a surface sampling program suitable for environmental monitoring in public schools. We find that the SDS/Thermo pipeline shows superior sensitivity and specificity, but that the VTM/PerkinElmer pipeline is still sufficient to support surface surveillance in any indoor setting with stable cohorts of occupants (e.g., schools, prisons, group homes, etc.) and may be used to leverage existing investments in infrastructure. IMPORTANCE The ongoing COVID-19 pandemic has claimed the lives of over 5 million people worldwide. Due to high density occupancy of indoor spaces for prolonged periods of time, schools are often of concern for transmission, leading to widespread school closings to combat pandemic spread when cases rise. Since pediatric clinical testing is expensive and difficult from a consent perspective, we have deployed surface sampling in SASEA (Safer at School Early Alert), which allows for detection of SARS-CoV-2 from surfaces within a classroom. In this previous work, we developed a high-throughput method which requires robotic automation and specific reagents that are often not available for public health laboratories such as the San Diego County Public Health Laboratory (SDPHL). Therefore, we benchmarked our method (Thermo pipeline) against SDPHL’s (PerkinElmer) more widely used method for the detection and prediction of SARS-CoV-2 exposure. While our method shows superior sensitivity (false-negative rate of 9% versus 27% for SDPHL), the SDPHL pipeline is sufficient to support surface surveillance in indoor settings. These findings are important since they show that existing investments in infrastructure can be leveraged to slow the spread of SARS-CoV-2 not in just the classroom but also in prisons, nursing homes, and other high-risk, indoor settings.
    Type of Medium: Online Resource
    ISSN: 2379-5077
    URL: Article
    DOI: 10.1128/msystems.00103-22
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2022
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  • 5
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    Analysis of SARS-CoV-2 RNA Persistence across Indoor Surface Materials Reveals Best Practices for Environmental Monitoring Programs
    American Society for Microbiology ; 2021
    In:  mSystems Vol. 6, No. 6 ( 2021-12-21)
    Details
    In: mSystems, American Society for Microbiology, Vol. 6, No. 6 ( 2021-12-21)
    Abstract: Environmental monitoring in public spaces can be used to identify surfaces contaminated by persons with coronavirus disease 2019 (COVID-19) and inform appropriate infection mitigation responses. Research groups have reported detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces days or weeks after the virus has been deposited, making it difficult to estimate when an infected individual may have shed virus onto a SARS-CoV-2-positive surface, which in turn complicates the process of establishing effective quarantine measures. In this study, we determined that reverse transcription-quantitative PCR (RT-qPCR) detection of viral RNA from heat-inactivated particles experiences minimal decay over 7 days of monitoring on eight out of nine surfaces tested. The properties of the studied surfaces result in RT-qPCR signatures that can be segregated into two material categories, rough and smooth, where smooth surfaces have a lower limit of detection. RT-qPCR signal intensity (average quantification cycle [ Cq ]) can be correlated with surface viral load using only one linear regression model per material category. The same experiment was performed with untreated viral particles on one surface from each category, with essentially identical results. The stability of RT-qPCR viral signal demonstrates the need to clean monitored surfaces after sampling to establish temporal resolution. Additionally, these findings can be used to minimize the number of materials and time points tested and allow for the use of heat-inactivated viral particles when optimizing environmental monitoring methods. IMPORTANCE Environmental monitoring is an important tool for public health surveillance, particularly in settings with low rates of diagnostic testing. Time between sampling public environments, such as hospitals or schools, and notifying stakeholders of the results should be minimal, allowing decisions to be made toward containing outbreaks of coronavirus disease 2019 (COVID-19). The Safer At School Early Alert program (SASEA) ( https://saseasystem.org/ ), a large-scale environmental monitoring effort in elementary school and child care settings, has processed 〉 13,000 surface samples for SARS-CoV-2, detecting viral signals from 574 samples. However, consecutive detection events necessitated the present study to establish appropriate response practices around persistent viral signals on classroom surfaces. Other research groups and clinical labs developing environmental monitoring methods may need to establish their own correlation between RT-qPCR results and viral load, but this work provides evidence justifying simplified experimental designs, like reduced testing materials and the use of heat-inactivated viral particles.
    Type of Medium: Online Resource
    ISSN: 2379-5077
    URL: Article
    DOI: 10.1128/mSystems.01136-21
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2021
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  • 6
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    SARS-CoV-2 Distribution in Residential Housing Suggests Contact Deposition and Correlates with Rothia sp.
    American Society for Microbiology ; 2022
    In:  mSystems Vol. 7, No. 3 ( 2022-06-28)
    Details
    In: mSystems, American Society for Microbiology, Vol. 7, No. 3 ( 2022-06-28)
    Abstract: Monitoring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces is emerging as an important tool for identifying past exposure to individuals shedding viral RNA. Our past work demonstrated that SARS-CoV-2 reverse transcription-quantitative PCR (RT-qPCR) signals from surfaces can identify when infected individuals have touched surfaces and when they have been present in hospital rooms or schools. However, the sensitivity and specificity of surface sampling as a method for detecting the presence of a SARS-CoV-2 positive individual, as well as guidance about where to sample, has not been established. To address these questions and to test whether our past observations linking SARS-CoV-2 abundance to Rothia sp. in hospitals also hold in a residential setting, we performed a detailed spatial sampling of three isolation housing units, assessing each sample for SARS-CoV-2 abundance by RT-qPCR, linking the results to 16S rRNA gene amplicon sequences (to assess the bacterial community at each location), and to the Cq value of the contemporaneous clinical test. Our results showed that the highest SARS-CoV-2 load in this setting is on touched surfaces, such as light switches and faucets, but a detectable signal was present in many untouched surfaces (e.g., floors) that may be more relevant in settings, such as schools where mask-wearing is enforced. As in past studies, the bacterial community predicts which samples are positive for SARS-CoV-2, with Rothia sp. showing a positive association. IMPORTANCE Surface sampling for detecting SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is increasingly being used to locate infected individuals. We tested which indoor surfaces had high versus low viral loads by collecting 381 samples from three residential units where infected individuals resided, and interpreted the results in terms of whether SARS-CoV-2 was likely transmitted directly (e.g., touching a light switch) or indirectly (e.g., by droplets or aerosols settling). We found the highest loads where the subject touched the surface directly, although enough virus was detected on indirectly contacted surfaces to make such locations useful for sampling (e.g., in schools, where students did not touch the light switches and also wore masks such that they had no opportunity to touch their face and then the object). We also documented links between the bacteria present in a sample and the SARS-CoV-2 virus, consistent with earlier studies.
    Type of Medium: Online Resource
    ISSN: 2379-5077
    URL: Article
    DOI: 10.1128/msystems.01411-21
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2022
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  • 7
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    Sentinel Cards Provide Practical SARS-CoV-2 Monitoring in School Settings
    American Society for Microbiology ; 2022
    In:  mSystems Vol. 7, No. 4 ( 2022-08-30)
    Details
    In: mSystems, American Society for Microbiology, Vol. 7, No. 4 ( 2022-08-30)
    Abstract: A promising approach to help students safely return to in person learning is through the application of sentinel cards for accurate high resolution environmental monitoring of SARS-CoV-2 traces indoors. Because SARS-CoV-2 RNA can persist for up to a week on several indoor surface materials, there is a need for increased temporal resolution to determine whether consecutive surface positives arise from new infection events or continue to report past events. Cleaning sentinel cards after sampling would provide the needed resolution but might interfere with assay performance. We tested the effect of three cleaning solutions (BZK wipes, Wet Wipes, RNase Away) at three different viral loads: “high” (4 × 10 4 GE/mL), “medium” (1 × 10 4 GE/mL), and “low” (2.5 × 10 3 GE/mL). RNase Away, chosen as a positive control, was the most effective cleaning solution on all three viral loads. Wet Wipes were found to be more effective than BZK wipes in the medium viral load condition. The low viral load condition was easily reset with all three cleaning solutions. These findings will enable temporal SARS-CoV-2 monitoring in indoor environments where transmission risk of the virus is high and the need to avoid individual-level sampling for privacy or compliance reasons exists. IMPORTANCE Because SARS-CoV-2, the virus that causes COVID-19, persists on surfaces, testing swabs taken from surfaces is useful as a monitoring tool. This approach is especially valuable in school settings, where there are cost and privacy concerns that are eliminated by taking a single sample from a classroom. However, the virus persists for days to weeks on surface samples, so it is impossible to tell whether positive detection events on consecutive days are a persistent signal or new infectious cases and therefore whether the positive individuals have been successfully removed from the classroom. We compare several methods for cleaning “sentinel cards” to show that this approach can be used to identify new SARS-CoV-2 signals day to day. The results are important for determining how to monitor classrooms and other indoor environments for SARS-CoV-2 virus.
    Type of Medium: Online Resource
    ISSN: 2379-5077
    URL: Article
    DOI: 10.1128/msystems.00109-22
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2022
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  • 8
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    Maximizing the potential of high-throughput next-generation sequencing through precise normalization based on read count distribution
    American Society for Microbiology ; 2023
    In:  mSystems
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    In: mSystems, American Society for Microbiology
    Abstract: High-throughput next generation sequencing (NGS) has significantly contributed to the field of genomics; however, further improvements can maximize the potential of this important tool. Uneven sequencing of samples in a multiplexed run is a common issue that leads to unexpected extra costs or low-quality data. To mitigate this problem, we introduce a normalization method based on read counts rather than library concentration. This method allows for an even distribution of features of interest across samples, improving the statistical power of data sets and preventing the financial loss associated with resequencing libraries. This method optimizes NGS, which already has huge importance across many areas of biology.
    Type of Medium: Online Resource
    ISSN: 2379-5077
    URL: Article
    DOI: 10.1128/msystems.00006-23
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2023
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  • 9
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    Handwashing and Detergent Treatment Greatly Reduce SARS-CoV-2 Viral Load on Halloween Candy Handled by COVID-19 Patients
    American Society for Microbiology ; 2020
    In:  mSystems Vol. 5, No. 6 ( 2020-12-22)
    Details
    In: mSystems, American Society for Microbiology, Vol. 5, No. 6 ( 2020-12-22)
    Abstract: Although SARS-CoV-2 is primarily transmitted by respiratory droplets and aerosols, transmission by fomites remains plausible. During Halloween, a major event for children in numerous countries, SARS-CoV-2 transmission risk via candy fomites worries many parents. To address this concern, we enrolled 10 recently diagnosed asymptomatic or mildly/moderately symptomatic COVID-19 patients to handle typical Halloween candy (pieces individually wrapped) under three conditions: normal handling with unwashed hands, deliberate coughing and extensive touching, and normal handling following handwashing. We then used a factorial design to subject the candies to two posthandling treatments: no washing (untreated) and household dishwashing detergent. We measured SARS-CoV-2 load by reverse transcriptase quantitative PCR (RT-qPCR) and loop-mediated isothermal amplification (LAMP). From the candies not washed posthandling, we detected SARS-CoV-2 on 60% of candies that were deliberately coughed on, 60% of candies normally handled with unwashed hands, but only 10% of candies handled after hand washing. We found that treating candy with dishwashing detergent reduced SARS-CoV-2 load by 62.1% in comparison to untreated candy. Taken together, these results suggest that although the risk of transmission of SARS-CoV-2 by fomites is low even from known COVID-19 patients, viral RNA load can be reduced to near zero by the combination of handwashing by the infected patient and ≥1 min detergent treatment after collection. We also found that the inexpensive and fast LAMP protocol was more than 80% concordant with RT-qPCR. IMPORTANCE The COVID-19 pandemic is leading to important tradeoffs between risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and mental health due to deprivation from normal activities, with these impacts being especially profound in children. Due to the ongoing pandemic, Halloween activities will be curtailed as a result of the concern that candy from strangers might act as fomites. Here, we demonstrate that these risks can be mitigated by ensuring that, prior to handling candy, the candy giver washes their hands and, after receipt, by washing candy with household dishwashing detergent. Even in the most extreme case, with candy deliberately coughed on by known COVID-19 patients, viral load was reduced dramatically after washing with household detergent. We conclude that with reasonable precautions, even if followed only by either the candy giver or the candy recipient, the risk of viral transmission by this route is very low.
    Type of Medium: Online Resource
    ISSN: 2379-5077
    URL: Article
    DOI: 10.1128/mSystems.01074-20
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2020
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  • 10
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    Quantifying Live Microbial Load in Human Saliva Samples over Time Reveals Stable Composition and Dynamic Load
    American Society for Microbiology ; 2021
    In:  mSystems Vol. 6, No. 1 ( 2021-02-23)
    Details
    In: mSystems, American Society for Microbiology, Vol. 6, No. 1 ( 2021-02-23)
    Abstract: Evaluating microbial community composition through next-generation sequencing has become increasingly accessible. However, metagenomic sequencing data sets provide researchers with only a snapshot of a dynamic ecosystem and do not provide information about the total microbial number, or load, of a sample. Additionally, DNA can be detected long after a microorganism is dead, making it unsafe to assume that all microbial sequences detected in a community came from living organisms. By combining relic DNA removal by propidium monoazide (PMA) with microbial quantification with flow cytometry, we present a novel workflow to quantify live microbial load in parallel with metagenomic sequencing. We applied this method to unstimulated saliva samples, which can easily be collected longitudinally and standardized by passive collection time. We found that the number of live microorganisms detected in saliva was inversely correlated with salivary flow rate and fluctuated by an order of magnitude throughout the day in healthy individuals. In an acute perturbation experiment, alcohol-free mouthwash resulted in a massive decrease in live bacteria, which would have been missed if we did not consider dead cell signal. While removing relic DNA from saliva samples did not greatly impact the microbial composition, it did increase our resolution among samples collected over time. These results provide novel insight into the dynamic nature of host-associated microbiomes and underline the importance of applying scale-invariant tools in the analysis of next-generation sequencing data sets. IMPORTANCE Human microbiomes are dynamic ecosystems often composed of hundreds of unique microbial taxa. To detect fluctuations over time in the human oral microbiome, we developed a novel workflow to quantify live microbial cells with flow cytometry in parallel with next-generation sequencing, and applied this method to over 150 unstimulated, timed saliva samples. Microbial load was inversely correlated with salivary flow rate and fluctuated by an order of magnitude within a single participant throughout the day. Removing relic DNA improved our ability to distinguish samples over time and revealed that the percentage of sequenced bacteria in a given saliva sample that are alive can range from nearly 0% up to 100% throughout a typical day. These findings highlight the dynamic ecosystem of the human oral microbiome and the benefit of removing relic DNA signals in longitudinal microbiome study designs.
    Type of Medium: Online Resource
    ISSN: 2379-5077
    URL: Article
    DOI: 10.1128/mSystems.01182-20
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2021
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