Quantifying the contributions of possible environmental sources (\"sources\") to a specific microbial community (\"sink\") is a classical problem in microbiology known as microbial source tracking (MST). Solving the MST problem will not only help us understand how microbial communities were formed, but also have far-reaching applications in pollution control, public health, and forensics. MST methods generally fall into two categories: target-based methods (focusing on the detection of source-specific indicator species or chemicals); and community-based methods (using community structure to measure similarity between sink samples and potential source environments). As next-generation sequencing becomes a standard community-assessment method in microbiology, numerous community-based computational methods, referred to as MST solvers hereafter have been developed and applied to various real datasets to demonstrate their utility across different contexts. Yet, those MST solvers do not consider microbial interactions and priority effects in microbial communities. Here, we revisit the performance of several representative MST solvers. We show compelling evidence that solving the MST problem using existing MST solvers is impractical when ecological dynamics plays a role in community assembly. In particular, we clearly demonstrate that the presence of either microbial interactions or priority effects will render the MST problem mathematically unsolvable for MST solvers. We further analyze data from fecal microbiota transplantation studies, finding that the state-of-the-art MST solvers fail to identify donors for most of the recipients. Finally, we perform community coalescence experiments to demonstrate that the state-of-the-art MST solvers fail to identify the sources for most of the sinks. Our findings suggest that ecological dynamics imposes fundamental challenges in MST. Interpretation of results of existing MST solvers should be done cautiously.

Different types of inlet water are expected to affect microbial communities of lake ecosystems due to changing environmental conditions and the dispersal of species. However, knowledge of the effects of changes in environmental conditions and export of microbial assemblages on lake ecosystems is limited, especially for glacier-fed lakes. Here, we collected water samples from the surface water of a glacier-fed lake and its two fed streams on the Tibetan Plateau to investigate the importance of glacial and non-glacial streams as sources of diversity for lake bacterial communities. Results showed that the glacial stream was an important source of microorganisms in the studied lake, contributing 45.53% to the total bacterial community in the lake water, while only 19.14% of bacterial community in the lake water was seeded by the non-glacial stream. Bacterial communities were significantly different between the glacier-fed lake and its two fed streams. pH, conductivity, total dissolved solids, water temperature and total nitrogen had a significant effect on bacterial spatial turnover, and together explained 36.2% of the variation of bacterial distribution among habitats. Moreover, bacterial co-occurrence associations tended to be stronger in the lake water than in stream habitats. Collectively, this study may provide an important reference for assessing the contributions of different inlet water sources to glacier-fed lakes.

Identifying sediment phosphorus sources, the key to control eutrophication, is hindered in multi-source polluted urban rivers by the lack of appropriate methods and data resolution. Community-based microbial source tracking (MST) offers new insight, but the bacterial communities could be affected by environmental fluctuations during the migration with sediments, which might induce instability of MST results. Therefore, the effects of environmental-induced community succession on the stability of MST were compared in this study. Liangxi River, a highly eutrophic urban river, was selected as the study area where sediment phosphorus sources are difficult to track because of multi-source pollution and complicated hydrodynamic conditions. Spearman correlation analysis (P < 0.05) was conducted to recognize a close relationship between sediment, bacterial communities and phosphorus, verifying the feasibility of MST for identify sediment phosphorus sources. Two distinct microbial community fingerprints were constructed based on whether excluded 113 vulnerable species, which were identified by analyzing the differences of microorganisms across a concentration gradient of exogenous phosphorus input in microbial environmental response experiment. Because of the lower unknown proportion and relative standard deviations, MST results were more stable and reliable when based on the fingerprints excluding species vulnerable to phosphorus. This study presents a novel insight on how to identify sediment phosphorus sources in multi-source polluted urban river, and would help to develop preferential control strategies for eutrophication management.

Microbial source tracking (MST) technology represents an innovative approach employed to trace fecal contamination in environmental water systems. The performance of primers may be affected by amplification techniques, target primer categories, and regional differences. To investigate the influence of these factors on primer recognition performance, a meta-analysis was conducted on the application of MST in water environments using three databases: Web of Science, Scopus, and PubMed (n = 2291). After data screening, 46 studies were included in the final analysis. The investigation encompassed Polymerase Chain Reaction (PCR)/quantitative PCR (qPCR) methodologies, dye-based (SYBR)/probe-based (TaqMan) techniques, and geographical differences of a human host-specific (HF183) primer and other 21 additional primers. The results indicated that the primers analyzed were capable of differentiating host specificity to a certain degree. Nonetheless, by comparing sensitivity and specificity outcomes, it was observed that virus-based primers exhibited superior specificity and recognition capacity, as well as a stronger correlation with human pathogenicity in water environments compared to bacteria-based primers. This finding highlights an important direction for future advancements. Moreover, within the same category, qPCR did not demonstrate significant benefits over conventional PCR amplification methods. In comparing dye-based and probe-based techniques, it was revealed that the probe-based method\'s advantage lay primarily in specificity, which may be associated with the increased propensity of dye-based methods to produce false positives. Furthermore, the heterogeneity of the HF183 primer was not detected in China, Canada, and Singapore respectively, indicating a low likelihood of regional differences. The variation among the 21 other primers may be attributable to regional differences, sample sources, detection techniques, or alternative factors. Finally, we identified that economic factors, climatic conditions, and geographical distribution significantly influence primer performance.

Biofilm detachment contributes to water quality deterioration. However, the contributions of biofilm detachment from different pipes have not been quantified or compared. Following the introduction of partial reverse osmosis (RO) in drinking water production, this study analyzed particles at customers\' ends and tracked their origins to water distribution mains and service lines. For doing so, filter bags were installed in front of water meters to capture upstream detached particles, while biofilm from water main and service line were sampled by cutting pipe specimens. The results showed that elemental concentrations of the biofilm in mains were higher than those of service lines (54.3-268.5 vs. 27.1-44.4 μg/cm2), both dominated by Ca. Differently, filter bags were dominated by Fe/Mn (77.5-98.1%). After introducing RO, Ca significantly decreased in biofilms of mains but not service lines, but the released Fe/Mn rather than Ca arrived at customers\' ends. The ATP concentrations of service lines were higher than mains, which decreased on mains but increased in service lines after introducing RO. For the core ASVs, 13/24 were shared by service lines (17), mains (21), and filter bags (17), which were assigned mainly to Nitrospira spp., Methylomagnum spp., Methylocytis spp., and IheB2-23 spp. According to source tracking results, service lines contributed more than mains to the particulate material collected by filter bags (57.6 ± 13.2% vs. 13.0 ± 11.6%). To the best of our knowledge, the present study provides the first evidence of service lines\' direct and quantitative contributions to potential water quality deterioration at customers\' ends. This highlights the need for the appropriate management of long-neglected service line pipes, e.g., regarding material selection, length optimization, and proper regulation.

A metagenomics-based technological framework has been proposed for evaluating the potential and utility of FEAST as an ARG profile-based source apportionment tool. To this end, a large panel of metagenomic data sets was analyzed, associating with eight source types of ARGs in environments. Totally, 1089 different ARGs were found in the 604 source metagenomes, and 396 ARG indicators were identified as the source-specific fingerprints to characterize each of the source types. With the source fingerprints, predictive performance of FEAST was checked using \"leave-one-out\" cross-validation strategy. Furthermore, artificial sink communities were simulated to evaluate the FEAST for source apportionment of ARGs. The prediction of FEAST showed high accuracy values (0.933 ± 0.046) and specificity values (0.959 ± 0.041), confirming its suitability to discriminate samples from different source types. The apportionment results reflected well the expected output of artificial communities which were generated with different ratios of source types to simulate various contamination levels. Finally, the validated FEAST was applied to track the sources of ARGs in river sediments. Results showed STP effluents were the main contributor of ARGs, with an average contribution of 76 %, followed by sludge (10 %) and aquaculture effluent (2.7 %), which were basically consistent with the actual environment in the area.

Antibiotic resistance genes (ARGs) are abundantly shed in feces. Thus, it is crucial to identify their host sources so that ARG pollution can be effectively mitigated and aquatic ecosystems can be properly conserved. Here, spatiotemporal variations and sources of ARGs in the Longjiang watershed of South China were investigated by linking them with microbial source tracker (MST) indicators. The most frequently detected ARGs (>90%) were sulI, sulII, blaTEM, tetW, ermF, and the mobile element intI1. Spatial distribution analyses showed that tributaries contributed significantly more sulI, sulII, and ermF contamination to the Longjiang watershed than the main channel. MST indicator analysis revealed that the Longjiang watershed was contaminated mainly by human fecal pollution. Livestock- and poultry-associated fecal pollution significantly declined after the swine fever outbreak. The occurrence of most ARGs is largely explained by human fecal pollution. In contrast, pig fecal pollution might account for the prevalence of tetO. Moreover, combined human-pig fecal pollution contributed to the observed blaNDM-1 distribution in the Longjiang watershed. Subsequent analysis of the characteristics of MST markers disclosed that the relatively lower specificities of BacHum and Rum-2-Bac may lead to inaccurate results of tracking ARG pollution source. The present study determined spatiotemporal variations and ARG origins in the Longjiang watershed by combining MST markers. It also underscored the necessity of using multiple MST markers simultaneously to identify and characterize ARG pollution sources accurately.

Antimicrobial resistance (AMR) in the environment has attracted increasing attention as an emerging global threat to public health. Stone is an essential ecosystem in nature and also an important material for human society, having architectural and aesthetic values. However, little is known about the AMR in stone ecosystems, particularly in the stone monument, where antimicrobials are often applied against biodeterioration. Here, we provide the first detailed metagenomic study of AMR genes across different types of biodeteriorated stone monuments, which revealed abundant and diverse AMR genes conferring resistance to drugs (antibiotics), biocides, and metals. Totally, 132 AMR subtypes belonging to 27 AMR types were detected including copper-, rifampin-, and aminocoumarins-resistance genes, of which diversity was mainly explained by the spatial turnover (replacement of genes between samples) rather than nestedness (loss of nested genes between samples). Source track analysis confirms that stone resistomes are likely driven by anthropogenic activities across stone heritage areas. We also detected various mobile genetic elements (namely mobilome, e.g., prophages, plasmids, and insertion sequences) that could accelerate replication and horizontal transfer of AMR genes. Host-tracking analysis further identified multiple biodeterioration-related bacterial genera such as Pseudonocardia, Sphingmonas, and Streptomyces as the major hosts of resistome. Taken together, these findings highlight that stone microbiota is one of the natural reservoirs of antimicrobial-resistant hazards, and the diverse resistome and mobilome carried by active biodeteriogens may improve their adaptation on stone and even deactivate the antimicrobials applied against biodeterioration. This enhanced knowledge may also provide novel and specific avenues for environmental management and stone heritage protection.

The strong-flavor Baijiu (SFB) brewing workshop is a complex ecosystem with diverse microbiomes. As a potential source of microbiomes in fermentation, microbiota in the environmental microecology may affect the quality and flavor of SFB. Here, we report the collection of environmental microecological samples from three SFB workshops with different usage times (named 70a, 30a, and new, respectively). We used 16S rRNA and internal transcribed spacer (ITS) gene amplicon full-length sequencing to explore the microbial community structure in SFB. The SourceTracker tool was used to investigate links among fermentation samples, raw materials, and the environment and decipher the construction process in the workshop indoor environment. Lactobacillus acetotolerans was the most important bacterial genus in Zaopei after fermentation, whereas other types of samples exhibited different prokaryotic community structures. The composition of the fungal community was similar, with Saccharomycopsis fibuligera, Debaryomyces hansenii, Lichtheimia ramosa, Lichtheimia corymbifera, and Pichia kudriavzevii being the most abundant, and were detected in most samples. Further comparison of the microbiota in the workshop environment showed that the diversity of the microbiota in the indoor environment decreased, showing different clustering patterns under the influence of location. With increasing usage time, the contribution of deterministic processes to the assembly of the prokaryotic community increases, and the community structure tends to stabilize, exhibiting its own characteristics. SFB-fermenting resident functional fungi were the major components of the fungal community, and SourceTracker analysis also highlighted the contributions of Zaopei, Daqu, and tool surfaces as fungal sources. This study is the first to comprehensively monitor the microbial profile of the SFB production environment. This research can be extended to involve more complex spontaneous fermentation environment microbiota and has important implications for the control of spontaneous fermentation.

Microbial source tracking (MST) tools provide insights on fecal pollution levels in aquatic environments using predominantly quantitative PCR (qPCR) assays that target host-associated molecular marker genes. Existing wastewater-associated marker genes have shown limited or significant cross-reactions with non-human fecal samples. In this study, we mined the current Gut Phage Database (GPD) and designed a novel untreated wastewater-specific Bifidobacterium phage qPCR assay (i.e., Bifi assay). The sensitivity and specificity of the Bifi marker genes were assessed by collectively analyzing untreated (n = 33) and treated (n = 15) wastewater and non-human fecal samples (i.e., Rabbit, mouse, cow, horse, pig, chicken, sheep, dog, deer, kangaroos; n = 113) in Shenzhen, Guangdong Province, China and Brisbane, Australia. Bifi assay revealed 100% host-specificity against non-human fecal samples collected from Shenzhen and Brisbane. Furthermore, this marker gene was also detected in all untreated and treated wastewater samples, whose concentrations ranged from 5.54 to 6.83 log10 GC/L. In Shenzhen, the concentrations of Bifi marker gene were approximately two orders of magnitude lower than Bacteroides (HF183/BacR287 assay) and CrAssphage (CPQ_56 assay). The concentration of Bifi marker gene in untreated wastewater from Brisbane was 1.35 log10 greater than those in Shenzhen. Our results suggest that Bifi marker gene has the potential to detect and quantify the levels of human fecal pollution in Shenzhen and Brisbane. If additional detection sensitivity is required for environmental studies, Bifi marker gene should be paired with either CrAssphage or HF183/BacR287 marker genes.