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The control of nitrous oxide (N2O) emissions through nitrification and the optimization of maize yield are important in agricultural systems. However, within the semi-arid region, the impact of fertilization on the function of nitrification communities and its connection with N2O emissions in the rhizosphere soil is still unclear. Our study investigates the influence of fertilization treatments on the communities of ammonia-oxidizing bacteria (AOB) and the complete ammonia oxidizers of the Nitrospira known as comammox (CAOB) in a maize agroecosystem. Nitrous oxide production, potential nitrification activity (PNA), maize yield, and nitrogen use efficiency (NUE) were determined for the same samples. The fertilizer treatments included a control group without fertilization (NA), inorganic fertilizer (CF), organic fertilizer (SM), combined inorganic and organic fertilizer (SC), and maize straw (MS). The SC treatment indicated a lower cumulative N2O emission than the CF treatment in the 2020 and 2021 cropping seasons. The AOB community under the CF, MS, and SM treatments was predominantly composed of Nitrosospira cluster 3b, while the SC treatment was associated with the comammox Nitrospira clade A.1 lineage, related to key species such as Ca. Nitrospira inopinata and Ca. Nitrospira nitrificans. Network analysis demonstrated a positive potential for competitive interaction between hub taxonomy and distinct keystone taxa among AOB and comammox Nitrospira nitrifiers. The structural equation model further revealed a significant positive association between AOB nitrifiers and N2O emission, PNA, soil pH, SOC, NO3−-N, and DON under organic fertilization. The keystone taxa in the comammox Nitrospira nitrifier and network Module II exhibited a positive correlation with maize productivity and NUE, likely due to their functional activities stimulated by the SC treatment. It is noteworthy that the AOB community played a more significant role in driving nitrification compared to the composition of comammox Nitrospira. Collectively, combined inorganic and organic fertilizer (SC) treatment exhibits high potential for reducing N2O emissions, enhancing maize productivity, increasing NUE, and increasing the sustainability of the nitrogen dynamics of maize agroecosystems in the semi-arid Loess Plateau.

Nitrous oxide (N2O) emissions are a major source of gaseous nitrogen loss, causing environmental pollution. The low organic content in the Loess Plateau region, coupled with the high fertilizer demand of maize, further exacerbates these N losses. N fertilizers play a primary role in N2O emissions by influencing soil denitrifying bacteria, however, the underlying microbial mechanisms that contribute to N2O emissions have not been fully explored. Therefore, the research aimed to gain insights into the intricate relationships between N fertilization, soil denitrification, N2O emissions, potential denitrification activity (PDA), and maize nitrogen use efficiency (NUE) in semi-arid regions. Four nitrogen (N) fertilizer rates, namely N0, N1, N2, and N3 (representing 0, 100, 200, and 300 kg ha−1 yr.−1, respectively) were applied to maize field. The cumulative N2O emissions were 32 and 33% higher under N2 and 37 and 39% higher under N3 in the 2020 and 2021, respectively, than the N0 treatment. N fertilization rates impacted the abundance, composition, and network of soil denitrifying communities (nirS and nosZ) in the bulk and rhizosphere soil. Additionally, within the nirS community, the genera Cupriavidus and Rhodanobacter were associated with N2O emissions. Conversely, in the nosZ denitrifier, the genera Azospirillum, Mesorhizobium, and Microvirga in the bulk and rhizosphere soil reduced N2O emissions. Further analysis using both random forest and structural equation model (SEM) revealed that specific soil properties (pH, NO3−-N, SOC, SWC, and DON), and the presence of nirS-harboring denitrification, were positively associated with PDA activities, respectively, and exhibited a significant association to N2O emissions and PDA activities but expressed a negative effect on maize NUE. However, nosZ-harboring denitrification showed an opposite trend, suggesting different effects on these variables. Our findings suggest that N fertilization promoted microbial growth and N2O emissions by increasing the abundance of nirS and nosZ denitrifiers and altering the composition of their communities. This study provides new insights into the relationships among soil microbiome, maize productivity, NUE, and soil N2O emissions in semi-arid regions.

Associations between grasses and soil microorganisms can strongly influence plant community structures. However, the associations between grass productivity and diversity and soil microbes, as well as the patterns of co-occurrence between grass and microbes remain unclear. Here, we surveyed grass productivity and diversity, determined soil physicochemical, and sequenced soil archaea, bacteria and fungi by metabarcoding technology at 16 alpine grasslands. Using the Distance-decay relationship, Inter-Domain Ecological Network (IDEN), and Mantel tests, we investigated the relationship between grass productivity, diversity and microbial diversity, and the patterns of co-occurrence between grass and microbial inter-domain network in alpine grassland. We found the archaea richness, bacteria richness and Shannon, and fungi α-diversity were significantly negatively correlation with grass diversity, but archaea and bacteria diversity were positively correlation with grass productivity. Moreover, an increase in microbial β-diversity was observed along with increased discrepancy in grass diversity and productivity and soil variables. Variance partitioning analysis suggested that the contribution of grass productivity on microbial community was higher than that of soil variables and grass diversity, which implies that microbial community was more related to grass productivity. Inter-Domain Ecological Network showed that the grass species formed complex and stable ecological networks with some bacterial, archaeal, and fungal species, and the grass-fungal ecological networks showed the highest robustness, which indicated that soil fungi could better co-coexist with aboveground grass in alpine grasslands. Besides, the connectivity degrees of the grass-microbial network were significantly positively correlated with grass productivity, suggesting that the coexistence pattern of grasses and microbes had a positive feedback effect on the grass productivity. The results are important for establishing the regulatory mechanisms between plants and microorganisms in alpine grassland ecosystems.

Wetlands are natural sources of methane (CH4) emissions, providing the largest contribution to the atmospheric CH4 pool. Changes in the ecohydrological environment of coastal salt marshes, especially the surface inundation level, cause instability in the CH4 emission levels of coastal ecosystems. Although soil methane-associated microorganisms play key roles in both CH4 generation and metabolism, how other microorganisms regulate methane emission and their responses to inundation has not been investigated. Here, we studied the responses of prokaryotic, fungal and cercozoan communities following 5 years of inundation treatments in a wetland experimental site, and molecular ecological networks analysis (MENs) was constructed to characterize the interdomain relationship. The result showed that the degree of inundation significantly altered the CH4 emissions, and the abundance of the pmoA gene for methanotrophs shifted more significantly than the mcrA gene for methanogens, and they both showed significant positive correlations to methane flux. Additionally, we found inundation significantly altered the diversity of the prokaryotic and fungal communities, as well as the composition of key species in interactions within prokaryotic, fungal, and cercozoan communities. Mantel tests indicated that the structure of the three communities showed significant correlations to methane emissions (p

Microbial community succession during decomposition has been proven to be a useful tool for postmortem interval (PMI) estimation. Numerous studies have shown that the intestinal microbial community presented chronological changes after death and was stable in terrestrial corpses with different causes of death. However, the postmortem pattern of intestinal microbial community succession in cadavers retrieved from water remains unclear. For immersed corpses, the postmortem submersion interval (PMSI) is a useful indicator of PMI. To provide reliable estimates of PMSI in forensic investigations, we investigated the gut microbial community succession of corpses submersed in freshwater and explored its potential application in forensic investigation. In this study, the intestinal microbial community of mouse submersed in freshwater that died of drowning or CO2 asphyxia (i.e., postmortem submersion) were characterized by 16S rDNA amplification and high-throughput sequencing, followed by bioinformatic analyses. The results demonstrated that the chronological changes in intestinal bacterial communities were not different between the drowning and postmortem submersion groups. α-diversity decreased significantly within 14 days of decomposition in both groups, and the β-diversity bacterial community structure ordinated chronologically, inferring the functional pathway and phenotype. To estimate PMSI, a regression model was established by random forest (RF) algorithm based on the succession of postmortem microbiota. Furthermore, 15 genera, including Proteus, Enterococcus, and others, were selected as candidate biomarkers to set up a concise predicted model, which provided a prediction of PMSI [MAE (± SE) = 0.818 (± 0.165) d]. Overall, our present study provides evidence that intestinal microbial community succession would be a valuable marker to estimate the PMSI of corpses submerged in an aquatic habitat.

IntroductionBodies recovered from water, especially in the late phase of decomposition, pose difficulties to the investigating authorities. Various methods have been proposed for postmortem submersion interval (PMSI) estimation and drowning identification, but some limitations remain. Many recent studies have proved the value of microbiota succession in viscera for postmortem interval estimation. Nevertheless, the visceral microbiota succession and its application for PMSI estimation and drowning identification require further investigation.MethodsIn the current study, mouse drowning and CO2 asphyxia models were developed, and cadavers were immersed in freshwater for 0 to 14 days. Microbial communities in the liver and brain were characterized via 16S rDNA high-throughput sequencing.ResultsOnly livers and brains collected from 5 to 14 days postmortem were qualified for sequencing. There was significant variation between microbiota from liver and brain. Differences in microbiota between the cadavers of mice that had drowned and those only subjected to postmortem submersion decreased over the PMSI. Significant successions in microbial communities were observed among the different subgroups within the late phase of the PMSI in livers and brains. Eighteen taxa in the liver which were mainly related to Clostridium_sensu_stricto and Aeromonas, and 26 taxa in the brain which were mainly belonged to Clostridium_sensu_stricto, Acetobacteroides, and Limnochorda, were selected as potential biomarkers for PMSI estimation based on a random forest algorithm. The PMSI estimation models established yielded accurate prediction results with mean absolute errors ± the standard error of 1.282 ± 0.189 d for the liver and 0.989 ± 0.237 d for the brain.ConclusionsThe present study provides novel information on visceral postmortem microbiota succession in corpses submerged in freshwater which sheds new light on PMSI estimation based on the liver and brain in forensic practice.

Postmortem interval (PMI) estimation has always been a major challenge in forensic science. Conventional methods for predicting PMI are based on postmortem phenomena, metabolite or biochemical changes, and insect succession. Because postmortem microbial succession follows a certain temporal regularity, the microbiome has been shown to be a potentially effective tool for PMI estimation in the last decade. Recently, artificial intelligence (AI) technologies shed new lights on forensic medicine through analyzing big data, establishing prediction models, assisting in decision-making, etc. With the application of next-generation sequencing (NGS) and AI techniques, it is possible for forensic practitioners to improve the dataset of microbial communities and obtain detailed information on the inventory of specific ecosystems, quantifications of community diversity, descriptions of their ecological function, and even their application in legal medicine. This review describes the postmortem succession of the microbiome in cadavers and their surroundings, and summarizes the application, advantages, problems, and future strategies of AI-based microbiome analysis for PMI estimation.

Denitrifying bacteria produce and utilize nitrous oxide (N2O), a potent greenhouse gas. However, there is little information on how organic fertilization treatments affect the denitrifying communities and N2O emissions in the semi-arid Loess Plateau. Here, we evaluated how the denitrifying communities are responsible for potential denitrification activity (PDA) and N2O emissions. A field experiment was conducted with five fertilization treatments, including no fertilization (CK), mineral fertilizer (MF), mineral fertilizer plus commercial organic fertilizer (MOF), commercial organic fertilizer (OFP), and maize straw (MSP). Our result showed that soil pH, soil organic carbon (SOC), and dissolved organic nitrogen (DON) were significantly increased under MSP treatment compared to MF treatment, while nitrate nitrogen (NO3−−N) followed the opposite trend. Organic fertilization treatments (MOF, OFP, and MSP treatments) significantly increased the abundance and diversity of nirS- and nosZ-harboring denitrifiers, and modified the community structure compared to CK treatment. The identified potential keystone taxa within the denitrifying bacterial networks belonged to the distinct genera. Denitrification potentials were significantly positively correlated with the abundance of nirS-harboring denitrifiers, rather than that of nirK- and nosZ-harboring denitrifiers. Random forest modeling and structural equation modeling consistently determined that the abundance, community composition, and network module I of nirS-harboring denitrifiers may contribute significantly to PDA and N2O emissions. Collectively, our findings highlight the ecological importance of the denitrifying communities in mediating denitrification potentials and the stimulatory impact of organic fertilization treatments on nitrogen dynamics in the semi-arid Loess Plateau.

Soil autotrophic bacteria play a crucial role in regulating CO2 fixation and crop productivity. However, the information is limited to how fertilization amendments alter soil autotrophic bacterial community, crop yield, and carbon emission efficiency (CEE). Here, we estimated the impact of the structure and co-occurrence network of soil autotrophic bacterial community on maize yield and CEE. A long-term field experiment was conducted with five fertilization treatments in semiarid Loess Plateau, including no amendment (NA), chemical fertilizer (CF), chemical fertilizer plus commercial organic fertilizer (SC), commercial organic fertilizer (SM), and maize straw (MS). The results showed that fertilization amendments impacted the structure and network of soil Calvin–Benson–Bassham (CBB) (cbbL) gene-carrying bacterial community via changing soil pH and NO3–N. Compared with no amendment, the cbbL-carrying bacterial diversity was increased under the SC, SM, and MS treatments but decreased under the CF treatment. Soil autotrophic bacterial network contained distinct microbial modules that consisted of closely associated microbial species. We detected the higher abundances of soil cbbL-carrying bacterial genus Xanthobacter, Bradyrhizobium, and Nitrosospira. Structural equation modeling further suggested that the diversity, composition, and network of autotrophic bacterial community had strongly positive relationships with CEE and maize yield. Taken together, our results suggest that soil autotrophic bacterial community may drive crop productivity and CEE, and mitigate the atmospheric greenhouse effect.

Diverse CRISPR-Cas systems constitute an indispensable part of the bacterial adaptive immune system against viral infections. However, to escape from this immune system, bacteriophages have also evolved corresponding anti-defense measures. We investigated the diversity of CRISPR-Cas systems and the presence of prophages in the genomes of 66 Bifidobacterium pseudocatenulatum strains. Our findings revealed a high occurrence of complete CRISPR-Cas systems (62%, 41/66) in the B. pseudocatenulatum genomes. Subtypes I-C, I-U and II-A, were found to be widespread in this species. No significant association was found between the number of bacterial CRISPR spacers and its host’s age. This study on prophages within B. pseudocatenulatum genomes revealed that prophage genes related to distinct functional modules became degraded at different levels, indicating that these prophages were not likely to enter lytic cycle spontaneously. Further, the evolutionary analysis of prophages in this study revealed that they might be derived from different phage ancestors. Notably, self-targeting phenomenon within B. pseudocatenulatum and Anti-CRISPR (Acr) coding genes in prophages was observed. Overall, our results indicate that the competition between B. pseudocatenulatum and phages is a major driving factor for the genomic diversity of both partners.

Constipation, which seriously affects living quality of people, is a common gastrointestinal disease. The engagement of the intestinal flora in the development of symptoms of constipation has been frequently hypothesized. In this study, constipated mice induced by loperamide were used to investige the alleviation of constipation by Bifidobacteria. Bifidobacteria was sorted out according to their adhesive properties into two groups. One group combined multiple strains of Bifidobacterium with adhesion property (CMB1), the other combined multiple strains of Bifidobacterium without adhesion property (CMB2). It was found that CMB1 can alleviate constipation more efficiently by improving the water, propionate and butyrate content in feces, and overall gastrointestinal transit time. Meanwhile, from the perspective of fecal microbiota, CMB1 alleviated constipation mainly by increasing the relative abundances of genera (Bifidobacterium, Lactobacillus, and Prevotella) associated with rapid bowel movement. From the perspective of cecal microbiota, CMB1 alleviated constipation mainly by increasing the relative abundances of genera Lactobacillus, Bacteroides, unclassified S24-7, Dorea, Ruminococcus, Coprococcus, and Rikenella, and decreasing the relative abundances of genera Oscillospira, Odoribacter and Unclassified F16, which are associated with methane production and colonic transit. Overall, changes of microbiota in caecum by CMB1 reflect the stage of constipation in mice more comprehensively than that in feces.

Galactooligosaccharides (GOS) are documented prebiotic compounds, but knowledge of the metabolic and regulatory mechanisms of GOS utilization by lactic acid bacteria is still limited. Here we used transcriptome and physiological analyses to investigate the differences in the logarithmic growth phase of Lactobacillus plantarum and L. plantarum ΔccpA metabolizing GOS or glucose as the sole source of carbohydrate. In total, 489 genes (16%) were differentially transcribed in the wild-type L. plantarum grown on glucose and GOS and the value is decreased to 7% due to the loss of ccpA. Only 6% genes were differentially expressed when the wild-type and the ccpA mutant were compared on GOS. Transcriptome data revealed that the carbon sources significantly affected the expression of several genes, and some of the genes were mediated by CcpA. In particular, lac and gal gene clusters resembled the corresponding clusters in L. acidophilus NCFM that are involved in GOS metabolism, indicating that these clusters may be participating in GOS utilization. Moreover, reverse transcription-PCR analysis showed that GOS-related gene clusters were organized in five independent polycistronic units. In addition, many commonalities were found between fructooligosaccharides and GOS metabolism in L. plantarum, including differentially expressed genes involved in oligosaccharide metabolism, conversion of metabolites, and changes in fatty acid biosynthesis. Overall, our findings provide new information on gene transcription and the metabolic mechanism associated with GOS utilization, and confirm that CcpA plays an important role in carbon metabolism regulation in L. plantarum.

Fructooligosaccharides (FOSs) metabolism in Lactobacillus plantarum is controlled by two gene clusters, and the global regulator catabolite control protein A (CcpA) may be involved in the regulation. To understand the mechanism, this study focused on the regulation relationships of CcpA toward target genes and the binding effects on the catabolite responsive element (cre). First, reverse transcription-PCR analysis of the transcriptional organization of the FOS-related gene clusters showed that they were organized in three independent polycistronic units. Diauxic growth, hierarchical utilization of carbohydrates and repression of FOS-related genes were observed in cultures containing FOS and glucose, suggesting carbon catabolite repression (CCR) control in FOS utilization. Knockout of ccpA gene eliminated these phenomena, indicating the principal role of this gene in CCR of FOS metabolism. Furthermore, six potential cre sites for CcpA binding were predicted in the regions of putative promoters of the two clusters. Direct binding was confirmed by electrophoretic mobility shift assays in vitro and chromatin immunoprecipitation in vivo. The results of the above studies suggest that CcpA is a vital regulator of FOS metabolism in L. plantarum and that CcpA-dependent CCR regulates FOS metabolism through the direct binding of CcpA toward the cre sites in the promoter regions of FOS-related clusters.

The control of nitrous oxide (N2O) emissions through nitrification and the optimization of maize yield are important in agricultural systems. However, within the semi-arid region, the impact of fertilization on the function of nitrification communities and its connection with N2O emissions in the rhizosphere soil is still unclear. Our study investigates the influence of fertilization treatments on the communities of ammonia-oxidizing bacteria (AOB) and the complete ammonia oxidizers of the Nitrospira known as comammox (CAOB) in a maize agroecosystem. Nitrous oxide production, potential nitrification activity (PNA), maize yield, and nitrogen use efficiency (NUE) were determined for the same samples. The fertilizer treatments included a control group without fertilization (NA), inorganic fertilizer (CF), organic fertilizer (SM), combined inorganic and organic fertilizer (SC), and maize straw (MS). The SC treatment indicated a lower cumulative N2O emission than the CF treatment in the 2020 and 2021 cropping seasons. The AOB community under the CF, MS, and SM treatments was predominantly composed of Nitrosospira cluster 3b, while the SC treatment was associated with the comammox Nitrospira clade A.1 lineage, related to key species such as Ca. Nitrospira inopinata and Ca. Nitrospira nitrificans. Network analysis demonstrated a positive potential for competitive interaction between hub taxonomy and distinct keystone taxa among AOB and comammox Nitrospira nitrifiers. The structural equation model further revealed a significant positive association between AOB nitrifiers and N2O emission, PNA, soil pH, SOC, NO3--N, and DON under organic fertilization. The keystone taxa in the comammox Nitrospira nitrifier and network Module II exhibited a positive correlation with maize productivity and NUE, likely due to their functional activities stimulated by the SC treatment. It is noteworthy that the AOB community played a more significant role in driving nitrification compared to the composition of comammox Nitrospira. Collectively, combined inorganic and organic fertilizer (SC) treatment exhibits high potential for reducing N2O emissions, enhancingmaize productivity, increasingNUE, and increasing the sustainability of the nitrogen dynamics ofmaize agroecosystems in the semi-arid Loess Plateau. [ABSTRACT FROM AUTHOR]

Nitrous oxide (N2O) emissions are a major source of gaseous nitrogen loss, causing environmental pollution. The low organic content in the Loess Plateau region, coupled with the high fertilizer demand of maize, further exacerbates these N losses. N fertilizers play a primary role in N2O emissions by influencing soil denitrifying bacteria, however, the underlying microbial mechanisms that contribute to N2O emissions have not been fully explored. Therefore, the research aimed to gain insights into the intricate relationships between N fertilization, soil denitrification, N2O emissions, potential denitrification activity (PDA), and maize nitrogen use efficiency (NUE) in semi-arid regions. Four nitrogen (N) fertilizer rates, namely N0, N1, N2, and N3 (representing 0, 100, 200, and 300 kg ha−1 yr.−1, respectively) were applied to maize field. The cumulative N2O emissions were 32 and 33% higher under N2 and 37 and 39% higher under N3 in the 2020 and 2021, respectively, than the N0 treatment. N fertilization rates impacted the abundance, composition, and network of soil denitrifying communities (nirS and nosZ) in the bulk and rhizosphere soil. Additionally, within the nirS community, the genera Cupriavidus and Rhodanobacter were associated with N2O emissions. Conversely, in the nosZ denitrifier, the genera Azospirillum, Mesorhizobium, and Microvirga in the bulk and rhizosphere soil reduced N2O emissions. Further analysis using both random forest and structural equation model (SEM) revealed that specific soil properties (pH, NO3−-N, SOC, SWC, and DON), and the presence of nirS-harboring denitrification, were positively associated with PDA activities, respectively, and exhibited a significant association to N2O emissions and PDA activities but expressed a negative effect on maize NUE. However, nosZ-harboring denitrification showed an opposite trend, suggesting different effects on these variables. Our findings suggest that N fertilization promoted microbial growth and N2O emissions by increasing the abundance of nirS and nosZ denitrifiers and altering the composition of their communities. This study provides new insights into the relationships among soil microbiome, maize productivity, NUE, and soil N2O emissions in semi-arid regions. [ABSTRACT FROM AUTHOR]

Denitrifying bacteria produce and utilize nitrous oxide (N2O), a potent greenhouse gas. However, there is little information on how organic fertilization treatments affect the denitrifying communities and N2O emissions in the semi-arid Loess Plateau. Here, we evaluated how the denitrifying communities are responsible for potential denitrification activity (PDA) and N2O emissions. A field experiment was conducted with five fertilization treatments, including no fertilization (CK), mineral fertilizer (MF), mineral fertilizer plus commercial organic fertilizer (MOF), commercial organic fertilizer (OFP), and maize straw (MSP). Our result showed that soil pH, soil organic carbon (SOC), and dissolved organic nitrogen (DON) were significantly increased under MSP treatment compared to MF treatment, while nitrate nitrogen (NO3 −−N) followed the opposite trend. Organic fertilization treatments (MOF, OFP, and MSP treatments) significantly increased the abundance and diversity of nirS- and nosZ-harboring denitrifiers, and modified the community structure compared to CK treatment. The identified potential keystone taxa within the denitrifying bacterial networks belonged to the distinct genera. Denitrification potentials were significantly positively correlated with the abundance of nirSharboring denitrifiers, rather than that of nirK- and nosZ-harboring denitrifiers. Random forest modeling and structural equation modeling consistently determined that the abundance, community composition, and network module I of nirS-harboring denitrifiers may contribute significantly to PDA and N2O emissions. Collectively, our findings highlight the ecological importance of the denitrifying communities in mediating denitrification potentials and the stimulatory impact of organic fertilization treatments on nitrogen dynamics in the semi-arid Loess Plateau. [ABSTRACT FROM AUTHOR]