Lithology and elevated temperature impact phoD-harboring bacteria on soil available P enhancing in subtropical forests.

Plants are generally limited by soil phosphorus (P) deficiency in forest ecosystems. Soil available P is influenced by lithology, temperature, and soil microbes. However, the interactive effects of these factors on soil P availability in subtropical forests remain unclear. To assess their impacts, we measured soil inorganic and available P fractions and the diversity, composition, and co-occurrence network of phoD-harboring bacteria in two contrasting forest soils (lithosols in karst forests and ferralsols in non-karst forests) in the subtropical regions of southwestern China across six temperature gradients. The present results showed that the complexities in composition and network and the diversity indices of phoD-harboring bacteria were higher in the karst forest soils than those in the non-karst forest soils, with marked differences in composition. In both types of forest soils, the complexities of composition and networks and the diversity indices were higher in the high-temperature regions (mean annual temperature (MAT) > 16 °C) compared to the low-temperature regions (MAT <16 °C). Soil total inorganic and available P contents were lower in the karst forest soils compared to the non-karst forest soils. Soil total available P contents were lower in the high temperature regions than those in the low temperature regions in both forest soils, whereas soil total inorganic P contents were contrary. Variance partitioning analysis showed that soil inorganic and available P fractions were predominantly explained by lithology and its interaction with soil microbes and climate. The present findings demonstrate that soil P availability in subtropical forests of southwestern China is influenced by lithology and temperature, which regulate the diversity, composition, and network connectivity of phoD-harboring bacteria. Furthermore, this study highlights the significance of controlling the composition of phoD-harboring bacteria for mitigating plant P deficiency in karst ecosystems.

Integrative analyses identify opportunistic pathogens of patients with lower respiratory tract infections based on metagenomic next-generation sequencing.

Lower respiratory tract infections (LRTIs) represent some of the most globally prevalent and detrimental diseases. Metagenomic next-generation sequencing (mNGS) technology has effectively addressed the requirement for the diagnosis of clinical infectious diseases. This study aimed at identifying and classifying opportunistic pathogens from the respiratory tract-colonizing microflora in LRTI patients using data acquired from mNGS analyses. A retrospective study was performed employing the mNGS data pertaining to the respiratory samples derived from 394 LRTIs patients. Linear discriminant analysis effect size (LEfSe) analysis was conducted to discern the discriminant bacteria. Receiver operating characteristic curves (ROC) were established to demonstrate discriminant bacterial behavior to distinguish colonization from infection. A total of 443 discriminant bacteria were identified and segregated into three cohorts contingent upon their correlation profiles, detection frequency, and relative abundance in order to distinguish pathogens from colonizing microflora. Among them, 119 emerging opportunistic pathogens (cohort 2) occupied an average area under the curve (AUC) of 0.976 for exhibiting the most prominent predictability in distinguishing colonization from infection, 39 were colonizing bacteria (cohort 1, 0.961), and 285 were rare opportunistic pathogens (cohort 3, 0.887). The LTRIs patients appeared modular in the form of cohorts depicting complex microbial co-occurrence networks, reduced diversity, and a high degree of antagonistic interactions in the respiratory tract microbiome. The study findings indicate that therapeutic interventions should target interaction networks rather than individual microbes, providing an innovative perspective for comprehending and combating respiratory infections. Conclusively, this study reports a profile of LRTIs-associated bacterial colonization and opportunistic pathogens in a relatively large-scale cohort, which might serve as a reference panel for the interpretation of mNGS results in clinical practice.

Quantitative proteomics revealed protein biomarkers to distinguish malignant pleural effusion from benign pleural effusion.

To identify protein biomarkers capable of early prediction regarding the distinguishing malignant pleural effusion (MPE) from benign pleural effusion (BPE) in patients with lung disease. A four-dimensional data independent acquisition (4D-DIA) proteomic was performed to determine the differentially expressed proteins in samples from 20 lung adenocarcinoma MPE and 30 BPE. The significantly differential expressed proteins were selected for Gene Ontology (GO) enrichment and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. Protein biomarkers with high capability to discriminate MPE from BPE patients were identified by Random Forest (RF) algorithm prediction model, whose diagnostic and prognostic efficacy in primary tumors were further explored in public datasets, and were validated by ELISA experiment. 50 important proteins (30 up-regulated and 20 down-regulated) were selected out as potential markers to distinguish the MPE from BPE group. GO analysis revealed that those proteins involving the most important cell component is extracellular space. KEGG analysis identified the involvement of cellular adhesion molecules pathway. Furthermore, the Area Under Curve (AUC) of these proteins were ranged from 0.717 to 1.000，with excellent diagnostic properties to distinguish the MPE. Finally, significant survival and gene and protein expression analysis demonstrated BPIFB1, DPP4, HPRT1 and ABI3BP had high discriminating values. SIGNIFICANCE: We performed a 4D-DIA proteomics to determine the differentially expressed proteins in pleural effusion samples from MPE and BPE. Some potential protein biomarkers were identified to distinguish the MPE from BPE patients., which may provide helpful diagnostic and therapeutic insights for lung cancer. This is significant because the median survival time of patients with MPE is usually 4-12 months, thus, it is particularly important to diagnose MPE early to start treatments promptly. The most common causes of MPE are lung cancers, while pneumonia and tuberculosis are the main causes of BPE. If more diagnostic markers could be identified periodically, there would be an important significance to clinical diagnose and treatment with drugs in lung cancer patients.

Vegetation recovery reshapes the composition and enhances the network connectivity of phoD-harboring microorganisms to promote P availability in a karst ecosystem.

Soil phoD-harboring microorganisms can facilitate phosphorus (P) transformation and increase the available P (AP) in P-limited soils; however, the mechanism by which these microorganisms enhance AP throughout the vegetation recovery process of karst ecosystems is poorly understood. Accordingly, this study investigates the effect of vegetation recovery on soil AP and the community composition and network connectivity of phoD-harboring microorganisms to elucidate the mechanism by which phoD-harboring microorganisms enhance soil AP in the four vegetation recovery stages (i.e., grassland, shrubland, shrub-arbor forest, and arbor forest) in a karst ecosystem. Results show that soil total P, AP, and microbial biomass P concentrations, as well as alkaline phosphatase activities, litter and soil nutrients, and plant diversity indices (Shannon-Wiener and Pielou) increase with advancing vegetation recovery. Moreover, the diversity indices (Shannon-Wiener and Simpson) and network complexity of the phoD-harboring microorganisms also increase with advancing vegetation recovery, leading to distinct communities among the four recovery stages. Rhizobiales, Pseudomonadales, and Burkholderiales comprise the dominant phoD-harboring microorganism orders. The relative abundances of Pseudomonadales and Burkholderiales increase with advancing vegetation recovery; Rhizobiales is the highest in shrubland and the lowest in grassland. The structural equation model results show that advanced vegetation recovery is associated with increased plant diversity, litter nutrients, and soil nutrients. The network connectivity is enhanced with advancing vegetation recovery accompanied by increasing soil phosphatase activity and P availability. These results suggest that regulating the phoD-harboring microorganism composition and network connectivity is essential to alleviate plant P limitation in karst ecosystems.

Water quality and microecosystem of water tanks in karst mountainous area, Southwest China.

Karst mountainous areas in Southwest China, the world's largest bare karst area, are faced with growing water shortages. Rainwater harvesting plays an important role in alleviating water shortage. However, there remains a substantial gap in the research regarding the water quality of tanks. Water samples were seasonally collected from ten tanks to investigate the physicochemical properties, microbial communities, and their key influencing factors. The result showed that pH, turbidity, chroma, DOC, and CODMn exceeded drinking water guidelines. The alkaline pH value and the deterioration of sensory properties was the main feature of tank water, from which the over-standard rate of the uncleaned water tanks was higher. Moreover, principal component analyses suggested that tank water quality was influenced by human activities, catchment areas, and material cycling processes within the tanks, of which in-tank microbial activities were the most important driving factors in water quality variation. Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, Firmicutes, and Verrucomicrobia were the predominant bacterial phyla in water tanks. Acinetobacter, Cyanobium-PCC-6307, CL500-29-marine-group, Candidatus-Aquiluna, and Exiguobacterium were the most abundant genera. The bacterial communities were significantly affected by the management practices. Higher relative abundance of Cyanobacteria and lower relative abundance of Proteobacteria was detected in the uncleaned tanks, which was a sign of tank water quality deterioration. The microbial community structure was closely related to the environmental factors. There was evidence that the water quality was affected by the existence of a microecosystem dominated by photosynthetic microorganisms in the water tanks. In addition, Acinetobacter, Enterobacter, Pseudomonas, and Legionella identified as the potential opportunistic pathogenic genera were frequently detected but the relative abundances except Acinetobacter were low in the tanks. Overall, our findings indicated that management style influences water quality and bacterial communities of tank water.