Responses of skin and salivary microbiome to different environmental exposures.

A multiplex microbial profiling system for the identification of the source of body fluid and skin samples

Determining the time since deposition (TsD) and sex of saliva stains is crucial for revealing the time of the crime's occurrence and clarifying the nature of the crime. This process not only shortens the time required to solve the case but also helps narrow down the scope of investigation, thereby enhancing the efficiency of case resolution. Currently, the forensic study of the microbial composition in long-term saliva stains remains a relatively underexplored field. The purpose of this study was to explore the succession pattern of long-placed human saliva stains microbial communities and identify relevant microbial markers for estimating TsD and identifying the sex of the donor, in order to be an effective alternative tool for solving practical forensic cases. Therefore, in this study, saliva stains exposed to indoor environmental conditions for up to 140days were collected and 16S rRNA full-length sequencing was performed using single-molecule real-time sequencing technology based on the PacBio sequencing platform. The study reveals that after 140days of placement, the relative abundance of Firmicutes significantly decreased (p = 0.00304). At the genus level, the relative abundances of Streptococcus (p = 0.0008), Rothia (p = 0.0448), Gemella (p = 0.016), and Veillonella (p = 0.0208) also significantly decreased. Additionally, significant differences were found in the microbial communities between saliva stains from males and females (p = 0.00013). Then, we constructed a TsD estimating model for microbial community markers based on random forest, and the results showed that the mean absolute error was 9.59days, and the accuracy of sex classification model based on stepwise logistic regression model and 4 bacterial markers was 84.21%. This indicates that saliva stains that have been in place for a long time still retain significant forensic value, and microbial markers can be used to determine the time since deposition (TsD) of dried saliva stains as well as to identify the sex of the donor.

ABSTRACTUnraveling the drivers controlling the response and adaptation of biological communities to environmental change, especially anthropogenic activities, is a central but poorly understood issue in ecology and evolution. Comparative genomics studies suggest that lateral gene transfer (LGT) is a major force driving microbial genome evolution, but its role in the evolution of microbial communities remains elusive. To delineate the importance of LGT in mediating the response of a groundwater microbial community to heavy metal contamination, representative Rhodanobacter reference genomes were sequenced and compared to shotgun metagenome sequences. 16S rRNA gene-based amplicon sequence analysis indicated that Rhodanobacter populations were highly abundant in contaminated wells with low pHs and high levels of nitrate and heavy metals but remained rare in the uncontaminated wells. Sequence comparisons revealed that multiple geochemically important genes, including genes encoding Fe2+/Pb2+ permeases, most denitrification enzymes, and cytochrome c553, were native to Rhodanobacter and not subjected to LGT. In contrast, the Rhodanobacter pangenome contained a recombinational hot spot in which numerous metal resistance genes were subjected to LGT and/or duplication. In particular, Co2+/Zn2+/Cd2+ efflux and mercuric resistance operon genes appeared to be highly mobile within Rhodanobacter populations. Evidence of multiple duplications of a mercuric resistance operon common to most Rhodanobacter strains was also observed. Collectively, our analyses indicated the importance of LGT during the evolution of groundwater microbial communities in response to heavy metal contamination, and a conceptual model was developed to display such adaptive evolutionary processes for explaining the extreme dominance of Rhodanobacter populations in the contaminated groundwater microbiome.

No studies have examined the effect of experimental warming on the microbial biomass and community composition of soil in agricultural ecosystem on the Qinghai-Tibet Plateau. Thus it is unclear whether the influences of experimental warming on microbial communities in soil are related to warming magnitude in croplands on this Plateau. This study performed warming experiment (control, low- and high-level) in a highland barley system of the Lhasa River in May 2014 to examine the correlation between the response of microbial communities in soil to warming and warming magnitude. Topsoil samples (0–10 and 10–20 cm) were collected on September 14, 2014. Experimental warming at both low and high levels significantly increased soil temperature by 1.02 °C and 1.59 °C, respectively at the depth of 15 cm. Phospho lipid fatty acid (PLFA) method was used to determine the microbial community in soil. The low-level experimental warming did not significantly affect the soil's total PLFA, fungi, bacteria, arbuscular mycorrhizal fungi (AMF), actinomycetes, gram-positive bacteria (G+), gram-negative bacteria (G–), protozoa, the ratio of fungi to bacteria (F/B ratio), and ratio of G+ to G– (G+/G– ratio) at the 0–10 and 10–20 cm depth. The low-level experimental warming also did not significantly alter the composition of microbial community in soil at the 0–10 and 10–20 cm depth. The high-level experimental warming significantly increased total PLFA by 74.4%, fungi by 78.0%, bacteria by 74.0%, AMF by 66.9%, actinomycetes by 81.4%, G+ by 67.0% and G– by 74.4% at the 0–10 cm depth rather than at 10–20 cm depth. The high-level experimental warming significantly altered microbial community composition in soil at the 0–10 cm depth rather than at 10-20 cm depth. Our findings suggest that the response of microbial communities in soil to warming varied with warming magnitudes in the highland barley system of the Lhasa River.

Second-generation biofuel crop miscanthus is one of the most promising plants tested for phytomanagement of contaminated sites. In this preliminary pot case study, the most used hybrid Miscanthus x giganteus was cultivated in three different real contaminated soils: agricultural soil contaminated with Cd; post-military soil slightly contaminated with Zn, Pb and Cd; and soil contaminated by petroleum industry with metals and hydrocarbons. The stress response of plants and soil microbial communities was monitored to receive data that are important for successful phytomanagement application. With metals only, the plant grew well, and chlorophyll fluorescence measurement proved their good vitality. Changes in leaf anatomy (leaf thickness and sclerenchyma cells area) were additionally determined in post-military soil compared to agricultural. On the contrary, in petroleum-contaminated soil, the biomass yield was too reduced and also physiological parameters were significantly decreased. The response of microbial communities also differed. In agricultural soil, no microbial stress was determined. In post-military soil, it became reduced during the experiment, and in petroleum contamination, it increased year-on-year. It could be concluded that miscanthus is suitable for cultivation in metals contaminated soils with potential for microbial communities support, but in soil contaminated by the petroleum industry, its application did not seem meaningful.

Rapid response of soil microbial communities from conventional, low input, and organic farming systems to a wet/dry cycle

Response of microbial communities colonizing salt marsh plants rhizosphere to copper oxide nanoparticles contamination and its implications for phytoremediation processes.

Gastric cancer continues to be one of the most significant cancers globally. Changes in microbiome composition and diversity have been implicated in gastric carcinogenesis; however, little is known about microbial community interactions and keystone species that drive these changes toward carcinogenesis. The aim of this work was to elucidate essential microbial interactions and community drivers that affect gastric carcinogenesis. We mined and utilized publicly available gastric microbiome data of adult human gastric biopsies with specific gastric diseases (gastric cancer, gastritis (chronic, superficial, atrophic), intestinal metaplasia) and healthy controls. We analysed the combined dataset using standard microbiome data analytics. Network topological properties of the various networks for gastric conditions revealed that the clustering coefficient decreased with increasing carcinogenesis. Higher modularity and lower averaged path were observed in the healthy control group as compared to the pre-cancerous and cancer groups. Sucinnate-producing and utilizing species, Bacteroides coprocola, Blautia wexlerae, and Phascolarctobacterium succinatutens, were also identified as important hubs in the precancerous conditions (gastritis and intestinal metaplasia) while nitrate-reducing bacteria Rothia mucilaginosa, Haemophilus haemolyticus, Haemophilus parainfluenzae, and Veillonella dispar were revealed as hubs in the gastric cancer group. Haemophilus parainfluenzae, which is an opportunistic oral pathogen, was identified as a potential network connector in three gastric conditions (healthy, intestinal metaplasia, and gastric cancer). Sphingobium fontiphilum and Rothia mucilaginosa were also revealed as keystone species for the control and cancer groups, respectively. The results from the clustering revealed distinct clusters in different gastric networks, indicating that microbial communities formed different functional groups during carcinogenesis. The random forest models also revealed pathogenic species Fusobacterium nucleatum be highly discriminative between healthy controls and gastric cancer groups.

Responses of microbial communities and metabolic activities in the rhizosphere during phytoremediation of Cd-contaminated soil

Insights into the spatiotemporal differences in tailings seepage pollution by assessing the diversity and metabolic functions of the soil microbial community

BackgroundThe molecular machinery of the complex microbiological cell factory of biomethane production is not fully understood. One of the process control elements is the regulatory role of hydrogen (H2). Reduction of carbon dioxide (CO2) by H2 is rate limiting factor in methanogenesis, but the community intends to keep H2 concentration low in order to maintain the redox balance of the overall system. H2 metabolism in methanogens becomes increasingly important in the Power-to-Gas renewable energy conversion and storage technologies.ResultsThe early response of the mixed mesophilic microbial community to H2 gas injection was investigated with the goal of uncovering the first responses of the microbial community in the CH4 formation and CO2 mitigation Power-to-Gas process. The overall microbial composition changes, following a 10 min excessive bubbling of H2 through the reactor, was investigated via metagenome and metatranscriptome sequencing. The overall composition and taxonomic abundance of the biogas producing anaerobic community did not change appreciably 2 hours after the H2 treatment, indicating that this time period was too short to display differences in the proliferation of the members of the microbial community. There was, however, a substantial increase in the expression of genes related to hydrogenotrophic methanogenesis of certain groups of Archaea. As an early response to H2 exposure the activity of the hydrogenotrophic methanogenesis in the genus Methanoculleus was upregulated but the hydrogenotrophic pathway in genus Methanosarcina was downregulated. The RT-qPCR data corroborated the metatranscriptomicResultsH2 injection also altered the metabolism of a number of microbes belonging in the kingdom Bacteria. Many Bacteria possess the enzyme sets for the Wood-Ljungdahl pathway. These and the homoacetogens are partners for syntrophic community interactions between the distinct kingdoms of Archaea and Bacteria.ConclusionsExternal H2 regulates the functional activity of certain Bacteria and Archaea. The syntrophic cross-kingdom interactions in H2 metabolism are important for the efficient operation of the Power-to-Gas process. Therefore, mixed communities are recommended for the large scale Power-to-Gas process rather than single hydrogenotrophic methanogen strains. Fast and reproducible response from the microbial community can be exploited in turn-off and turn-on of the Power-to-Gas microbial cell factories.

Responses of a microbial community in the completely autotrophic nitrogen removal over nitrite (CANON) process, which was shocked by a pH of 11.0 for 12 h, were investigated. During the recovery phase, the performance, anaerobic ammonia oxidation (anammox) activity, microbial community, and correlation of bacteria as well as the influencing factors were evaluated synchronously. The performance of the CANON process deteriorated rapidly with a nitrogen removal rate (NRR) of 0.13 kg·m−3·d−1, and Firmicutes, spore-forming bacteria, were the dominant phyla after alkaline shock. However, it could self-restore within 107 days after undergoing four stages, at which Planctomycetes became dominant with a relative abundance of 64.62%. Network analysis showed that anammox bacteria (Candidatus Jettenia, Kuenenia, and Brocadia) were positively related to some functional bacteria such as Nitrosomonas, SM1A02, and Calorithrix. Canonical correspondence analysis presented a strong correlation between the microbial community and influencing factors during the recovery phase. With the increase of nitrogen loading rate, the decrease of free nitrous acid and the synergistic effects, heme c content, specific anammox activity (SAA), NRR, and the abundance of dominant genus increased correspondingly. The increase of heme c content regulates the quorum sensing system, promotes the secretion of extracellular polymeric substances, and further improves SAA, NRR, and the relative abundance of the dominant genus. This study highlights some implications for the recovery of the CANON reactor after being exposed to an alkaline shock.

Microbial community changes in response to climate change drivers have the potential to alter the trajectory of important ecosystem functions. In this paper, we show that while microbial communities in peatland systems responded to manipulations of temperature and CO2 concentrations, these changes were not associated with similar responses in peat decomposition rates over 3 years. It is unclear however from our current studies whether this functional resiliency over 3 years will continue over the longer time scales relevant to peatland ecosystem functions.

Microbial community response of nitrifying sequencing batch reactors to silver, zero-valent iron, titanium dioxide and cerium dioxide nanomaterials

BackgroundDrowning diagnosis has long been a critical issue in forensic research, influenced by various factors such as the environment and decomposition time. While traditional methods such as diatom analysis have limitations in decomposed remains, microbial community profiling offers a promising alternative. With the advancement of high-throughput sequencing technology, forensic microbiology has become a prominent focus in the field, providing new research avenues for drowning diagnosis. During drowning, microbial communities enter the lung tissue along with the water.MethodsIn this study, using a murine model, we collected samples from three rivers at random sites at postmortem intervals (PMI) of 1, 4, and 7 days‌ to comprehensively evaluate the differences in microbial communities between mice subjected to drowning versus postmortem immersion.ResultsThe α-diversity analysis revealed that the observed Operational Taxonomic Units (OTUs) for the drowning group on day 1 was 234.77 ± 16.60, significantly higher than the postmortem immersion group (171.32 ± 9.22), indicating greater initial microbial richness in the drowning group. Additionally, Shannon index analysis showed a significant decline in evenness in the postmortem immersion group on day 7 (1.46 ± 0.09), whereas the drowning group remained relatively stable (2.38 ± 0.15), further indicating a rapid decrease in microbial diversity in the postmortem immersion group over time. PCoA analysis demonstrated that differences in microbial community composition between drowning and postmortem immersion groups were notably stable. Key microbial taxa differentiating the groups were identified through LEfSe analysis, with Enterococcaceae (family), Escherichia-Shigella (genus), and Proteus (genus), emerging as significant markers in drowning cases. A random forest model, trained using microbial community data, exhibited high predictive accuracy (AUC = 0.96) across locations and immersion times and identified microbial markers, including Enterococcaceae (family), Lactobacillales (order), Morganellaceae (family), as critical features influencing model performance.ConclusionThese findings underscore the potential of combining 16 S rRNA sequencing with machine learning as a powerful tool for drowning diagnosis, offering novel insights into forensic microbiology.