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1. Clean room microbiome complexity impacts planetary protection bioburden

   https://doi.org/10.1186/s40168-021-01159-x  

   Hendrickson, Ryan ; Urbaniak, Camilla ; Minich, Jeremiah J. ; Aronson, Heidi S. ; Martino, Cameron ; Stepanauskas, Ramunas ; Knight, Rob ; Venkateswaran, Kasthuri ( December 2021 , Microbiome)

   The Spacecraft Assembly Facility (SAF) at the NASA’s Jet Propulsion Laboratory is the primary cleanroom facility used in the construction of some of the planetary protection (PP)-sensitive missions developed by NASA, including the Mars 2020 Perseverance Rover that launched in July 2020. SAF floor samples (n=98) were collected, over a 6-month period in 2016 prior to the construction of the Mars rover subsystems, to better understand the temporal and spatial distribution of bacterial populations (total, viable, cultivable, and spore) in this unique cleanroom.

   Cleanroom samples were examined for total (living and dead) and viable (living only) microbial populations using molecular approaches and cultured isolates employing the traditional NASA standard spore assay (NSA), which predominantly isolated spores. The 130 NSA isolates were represented by 16 bacterial genera, of which 97% were identified as spore-formers via Sanger sequencing. The most spatially abundant isolate wasBacillus subtilis, and the most temporally abundant spore-former wasVirgibacillus panthothenticus. The 16S rRNA gene-targeted amplicon sequencing detected 51 additional genera not found in the NSA method. The amplicon sequencing of the samples treated with propidium monoazide (PMA), which would differentiate between viable and dead organisms, revealed a total of 54 genera: 46 viable non-spore forming genera and 8 viable spore forming genera in these samples. The microbial diversity generated by the amplicon sequencing corresponded to ~86% non-spore-formers and ~14% spore-formers. The most common spatially distributed genera wereSphinigobium,Geobacillus, andBacilluswhereas temporally distributed common genera wereAcinetobacter,Geobacilllus, andBacillus. Single-cell genomics detected 6 genera in the sample analyzed, with the most prominent beingAcinetobacter.

   This study clearly established that detecting spores via NSA does not provide a complete assessment for the cleanliness of spacecraft-associated environments since it failed to detect several PP-relevant genera that were only recovered via molecular methods. This highlights the importance of a methodological paradigm shift to appropriately monitor bioburden in cleanrooms for not only the aeronautical industry but also for pharmaceutical, medical industries, etc., and the need to employ molecular sequencing to complement traditional culture-based assays.

    

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2. Shotgun metagenomics and microscopy indicate diverse cyanophytes, other bacteria, and microeukaryotes in the epimicrobiota of a northern Chilean wetland Nostoc (Cyanobacteria)

   https://doi.org/10.1111/jpy.13084  

   Satjarak, Anchittha ; Graham, Linda E. ; Piotrowski, Michael J. ; Trest, Marie T. ; Wilcox, Lee W. ; Cook, Martha E. ; Knack, Jennifer J. ; Arancibia‐Avila, Patricia ; Collier, ed., J. ( December 2020 , Journal of Phycology)

   ProkaryoticNostoc, one of the world's most conspicuous and widespread algal genera (similar to eukaryotic algae, plants, and animals) is known to support a microbiome that influences host ecological roles. Past taxonomic characterizations of surface microbiota (epimicrobiota) of free‐livingNostocsampled from freshwater systems employed 16S rRNA genes, typically amplicons. We compared taxa identified from 16S, 18S, 23S, and 28S rRNA gene sequences filtered from shotgun metagenomic sequence and used microscopy to illuminate epimicrobiota diversity forNostocsampled from a wetland in the northern Chilean Altiplano. Phylogenetic analysis and rRNA gene sequence abundance estimates indicated that the host was related toNostoc punctiformePCC 73102. Epimicrobiota were inferred to include 18 epicyanobacterial genera or uncultured taxa, six epieukaryotic algal genera, and 66 anoxygenic bacterial genera, all having average genomic coverage ≥90X. The epicyanobacteriaGeitlerinemia,Oscillatoria,Phormidium, and an uncultured taxon were detected only by 16S rRNA gene;GloeobacterandPseudanabaenawere detected using 16S and 23S; andPhormididesmis,Neosynechococcus,Symphothece,Aphanizomenon,Nodularia,Spirulina,Nodosilinea,Synechococcus,Cyanobium, andAnabaena(the latter corroborated by microscopy), plus two uncultured cyanobacterial taxa (JSC12, O77) were detected only by 23S rRNA gene sequences. Three chlamydomonad and two heterotrophic stramenopiles genera were inferred from 18S; the streptophyte green algaChaetosphaeridium globosumwas detected by microscopy and 28S rRNA genes, but not 18S rRNA genes. Overall, >60% of epimicrobial taxa were detected by markers other than 16S rRNA genes. Some algal taxa observed microscopically were not detected from sequence data. Results indicate that multiple taxonomic markers derived from metagenomic sequence data and microscopy increase epimicrobiota detection.

    

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3. Cadaver Microbial Signatures of the Submandibular Glands and Thyroid for Forensic Investigations

   Sheree Finley, PhD* ; Matteo Moretti, MD ; Silvia Visonà, PhD ; Gulnaz Javan, PhD* ( January 2023 , Cadaver Microbial Signatures of the Submandibular Glands and Thyroid for Forensic Investigations)

   The study of the thyroid is an emerging topic, particularly in postmortem microbiome studies, due to the organ’s ability to affect the endocrine system. Also, the submandibular gland is a promising, emerging gland of study due to its position relative to the oral cavity. Previous thanatomicrobiome studies have demonstrated that bacteria belonging to the phyla Firmicutes, Proteobacteria, Bacteroides, and Pseudomonadota predominate internal organs and have been considered an important biomarker for postmortem interval. Further, Clostridium species that dominate in internal organs are linked to the hypoxic change that occurs after death, which leads to the switch of bacteria to become obligate anaerobes. Therefore, obligate anaerobes dominate the body after death due to their ability to thrive off fermentation products. 16S rRNA gene sequencing has been critical in thanatomicrobiome studies, which refers to the human microbiome (microorganisms within the body) after death. Currently, it has not been elucidated regarding the microorganisms that are associated with the decay of submandibular and thyroid glands. We hypothesized that through sequencing of the 16S rRNA gene of the submandibular and thyroid glands, the presence of Firmicutes and Proteobacteria will indicate potential biomarkers for postmortem interval. The present study revealed the postmortem microbial signatures of the submandibular and thyroid glands using the 16S rRNA gene, specifically the V3-V4 hypervariable regions, using universal primers 341F and 805R. We investigated a total of 37 cadavers obtained from ongoing criminal casework, 17 submandibular samples and 20 thyroid samples, and found that there is a correlation between microbial abundance in these postmortem glands. The predominating phyla of interest found in both glands were Firmicutes and Proteobacteria. The predominating genera were Paeniclostridium and Streptococcus in both glands, respectively. Further experimentation of the submandibular and thyroid glands will help to link oral thanatomicrobiome communities to “microbial clock” determinations, thus enhancing postmortem interval estimation. 

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4. Oral microbiome dysbiosis among cigarette smokers and smokeless tobacco users compared to non-users

   https://doi.org/10.1038/s41598-024-60730-2  

   Chattopadhyay, Suhana ; Malayil, Leena ; Chopyk, Jessica ; Smyth, Eoghan ; Kulkarni, Prachi ; Raspanti, Greg ; Thomas, Stephen B. ; Sapkota, Amir ; Mongodin, Emmanuel F. ; Sapkota, Amy R. ( May 2024 , Scientific Reports)

   Tobacco use significantly influences the oral microbiome. However, less is known about how different tobacco products specifically impact the oral microbiome over time. To address this knowledge gap, we characterized the oral microbiome of cigarette users, smokeless tobacco users, and non-users over 4 months (four time points). Buccal swab and saliva samples (n = 611) were collected from 85 participants. DNA was extracted from all samples and sequencing was carried out on an Illumina MiSeq, targeting the V3–V4 region of the 16S rRNA gene. Cigarette and smokeless tobacco users had more diverse oral bacterial communities, including a higher relative abundance ofFirmicutesand a lower relative abundance ofProteobacteria, when compared to non-users. Non-users had a higher relative abundance ofActinomyces, Granulicatella, Haemophilus, Neisseria, Oribacterium, Prevotella, Pseudomonas, Rothia, andVeillonellain buccal swab samples, compared to tobacco users. While the most abundant bacterial genera were relatively constant over time, some species demonstrated significant shifts in relative abundance between the first and last time points. In addition, some opportunistic pathogens were detected among tobacco users includingNeisseria subflava, Bulleidia mooreiandPorphyromonas endodontalis. Overall, our results provide a more holistic understanding of the structure of oral bacterial communities in tobacco users compared to non-users.

    

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5. No apparent correlation between honey bee forager gut microbiota and honey production

   https://doi.org/10.7717/peerj.1329  

   Horton, Melissa A. ; Oliver, Randy ; Newton, Irene L. ( January 2015 , PeerJ)

   null (Ed.)

   One of the best indicators of colony health for the European honey bee ( Apis mellifera ) is its performance in the production of honey. Recent research into the microbial communities naturally populating the bee gut raise the question as to whether there is a correlation between microbial community structure and colony productivity. In this work, we used 16S rRNA amplicon sequencing to explore the microbial composition associated with forager bees from honey bee colonies producing large amounts of surplus honey (productive) and compared them to colonies producing less (unproductive). As supported by previous work, the honey bee microbiome was found to be dominated by three major phyla: the Proteobacteria, Bacilli and Actinobacteria, within which we found a total of 23 different bacterial genera, including known “core” honey bee microbiome members. Using discriminant function analysis and correlation-based network analysis, we identified highly abundant members (such as Frischella and Gilliamella ) as important in shaping the bacterial community; libraries from colonies with high quantities of these Orbaceae members were also likely to contain fewer Bifidobacteria and Lactobacillus species (such as Firm-4). However, co-culture assays, using isolates from these major clades, were unable to confirm any antagonistic interaction between Gilliamella and honey bee gut bacteria. Our results suggest that honey bee colony productivity is associated with increased bacterial diversity, although this mechanism behind this correlation has yet to be determined. Our results also suggest researchers should not base inferences of bacterial interactions solely on correlations found using sequencing. Instead, we suggest that depth of sequencing and library size can dramatically influence statistically significant results from sequence analysis of amplicons and should be cautiously interpreted. 

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