Abundance Of Sequences Research Articles

Abstract 1121: Neutrophil Proteobacteria Sequences Increases After Open Aortic Surgery

Introduction: Bacterial extracellular vesicles (bEV) transport diverse cargoes, including nucleic acids, and play a crucial role during host-microbe interactions, including modifying host immune response. Neutrophil activation is prevalent in aortic disease pathogenesis, but the cause is unclear. The baseline neutrophilic bEV content and its dynamics are unknown and may provide insight into neutrophil activation in aortic disease. Research Question: Does open aortic surgery change neutrophil bEV content? Methods: Blood was collected pre and post-operatively from 6 patients undergoing open aortic surgery. Neutrophils were isolated using standard centrifugation techniques, and nucleic acids were purified. The V1-V3 16s rRNA segments were amplified with universal primers and sequenced using an Illumina MiSeq platform. Reads were processed in QIIME2 and aligned to reference banks of known bacterial sequences. Sequence abundance was analyzed with Kruskal-Wallis and Wilcoxon-rank tests. Results: The average patient age was 60.2 years, with 4 male patients and 4 current smokers. The most common phylum and genus represented in the neutrophil bacterial reads were Proteobacteria (Figure 1A) and Delftia , respectively. The relative abundance of Proteobacteria sequences increased overtime (p=0.042) from a median of 45.43% (IQR:35.3-52.0) to 70.8% (IQR:66.1-81.5, p=0.026) post-operatively, to 83.5% (IQR:60.7-89.7, p=0.004) on POD1 (Figure 1B). POD3 Proteobacteria sequence abundance was stable from POD1 at 81.4% (IQR:64.2-89.6). Conclusions: Neutrophils of patients with aortic disease rapidly change their bacterial sequence content in response to open aortic surgery. Bacteria in the phylum Proteobacteria change most dramatically and equilibrate between POD 1 and 3. Further studies will elucidate the impact changing bacterial sequence abundance and bEV content has on neutrophil activity and its relationship to disease pathogenesis.

Leveraging genomic signatures of oral microbiome-associated antibiotic resistance genes for diagnosing pancreatic cancer.

Growing evidence has increasingly suggested a potential linkage between the oral microbiome and various diseases, including pancreatic ductal adenocarcinoma (PDAC). However, the utilization of gene-level information derived from the oral microbiome for diagnosing PDAC remains unexplored. In this study, we sought to investigate the novel potential of leveraging genomic signatures associated with antibiotic resistance genes (ARGs) within the oral microbiome for the diagnosis of PDAC. By conducting an analysis of oral microbiome samples obtained from PDAC patients, we successfully identified specific ARGs that displayed distinct sequence abundance profiles correlated with the presence of PDAC. In the healthy group, three ARGs were found to be enriched, whereas 21 ARGs were enriched in PDAC patients. Remarkably, these ARGs from oral microbiome exhibited promising diagnostic capabilities for PDAC (AUROC = 0.79), providing a non-invasive and early detection method. Our findings not only provide novel modal data for diagnosing PDAC but also shed light on the intricate interplay between the oral microbiome and PDAC.

Elucidating the multichromosomal structure within the Brasenia schreberi mitochondrial genome through assembly and analysis

Brasenia schreberi, a plant species traditionally utilized in Chinese medicine and cuisine, represents an early evolutionary stage among flowering plants (angiosperms). While the plastid genome of this species has been published, its mitochondrial genome (mitogenome) has not been extensively explored, with a notable absence of thorough comparative analyses of its organellar genomes. In our study, we had assembled the entire mitogenome of B. schreberi utilizing the sequencing data derived from both Illumina platform and Oxford Nanopore. The B. schreberi mitogenome mostly exists as six circular DNA molecules, with the largest being 628,257 base pairs (bp) and the smallest 110,220 bp, amounting to 1.49 megabases (Mb). Then we annotated the mitogenome of B. schreberi. The mitogenome encompasses a total of 71 genes: 40 of these are coding proteins genes (PCGs), 28 are genes for transfer RNA (tRNA), and the remaining 3 are genes for ribosomal RNA (rRNA). In the analysis of codon usage, we noted a unique codon preference specific to each amino acid. The most commonly used codons exhibited an average RSCU of 1.36, indicating a noticeable bias in codon selection. In the repeat sequence analysis, a total of 553 simple sequence repeats (SSRs) were identified, 1,822 dispersed repeats (comprising 1,015 forward and 807 palindromic repeats), and 608 long terminal repeats (LTRs). Additionally, in the analysis of homologous sequences between organelle genomes, we detected 38 homologous sequences derived from the plastid genome, each exceeding 500 bp, within the B. schreberi mitochondrial genome. Notably, ten tRNA genes (trnC-GCA, trnM-CAU, trnI-CAU, trnQ-UUG, trnN-GUU, trnT-GGU, trnW-CCA, trnA-UGC, trnI-GAU, and trnV-GAC) appear to have been completely transferred from the chloroplast to the mitogenome. Utilizing the Deepred-mt to predict the RNA editing sites in the mitogenome, we have identified 675 high-quality RNA editing sites in the 40 mitochondrial PCGs. In the final stage of our study, we performed an analysis of colinearity and inferred the phylogenetic relationship of B. schreberi with other angiosperms, utilizing the mitochondrial PCGs as a basis. The results showed that the non-coding regions of the B. schreberi mitogenome are characterized by an abundance of repetitive sequences and exogenous sequences, and B. schreberi is more closely related with Euryale ferox.

Soil Fertility and Bacterial Community Composition in Response to the Composting of Biochar-Amended Chicken Manure

Amidst the burgeoning expanse of the poultry sector, the escalation of chicken manure production has ensued, potentially exacerbating ecological contamination. However, the application of chicken manure is bound to transmute the habitat of edaphic microorganisms, precipitating an alteration in the soil’s microbial consortium. The composting of biochar-amended chicken manure and wood chips (biochar composting products, BCPs) was used to improve Chinese cabbage (Brassica campestris L.) production and regulate soil properties and bacterial community structure. On the 40th day of Chinese cabbage growth, soil and Chinese cabbage were collected for laboratory analysis. The effects of different proportions of BCPs (0, 1%, 3%, 5% and 7% biochar) on soil fertility, enzyme activity, the microbial community and the growth of Chinese cabbage were studied under facility conditions. The results showed that the growth performance and quality of Chinese cabbage were significantly increased with increasing BCP ratios. Soil fertility indicators including pH, AN, AP, AK and SOM were significantly increased, except for the pH value in the 1% BCP group. The activities of phosphatase, catalase and urease were increased for all groups of BCP treatment. The soil microbial community response was significantly different, and the application of 5% and 7% BCPs reduced the abundance, diversity and evenness of soil bacteria. Chinese cabbage growth performance was positively correlated with an increase in BCP supplemental levels in the range of 3–5%. Also, the abundance, diversity and uniformity of the soil microbial community were improved in the 3% BCP treatment group. Therefore, the dominant bacterial phyla were Bacteroidetes, Actinobacteriota, Gemmatimonadota, Myxococcota, Bdellovibrionota and Firmicutes, especially the Bradyrhizobium of Proteobacteria. BCP treatment reduced the degradation of soil organic matter. In addition, it also improved the relative abundance of sequences associated with improving soil fertility. Collectively, these findings offer insights for the re-evaluation of application management strategies for BCP organic fertilizers.

Correlation of lesion severity with bacterial changes in Treponeme-Associated Hoof Disease from free-roaming wild elk (Cervus canadensis)

BackgroundTreponeme-Associated Hoof Disease (TAHD) is a polybacterial, multifactorial disease affecting free-ranging wild elk (Cervus canadensis) in the Pacific Northwest. Previous studies have indicated a bacterial etiology similar to digital dermatitis in livestock, including isolation of Treponema species from lesions. The lesions appear to progress rapidly from ulcerative areas in the interdigital space or along the coronary band to severe, ulcerative, necrotic, proliferative lesions under-running the hoof wall, perforating the sole, and contributing to hoof elongation, deformity, and overgrowth. Eventually the lesions undermine the laminal structure leading to sloughing of the hoof horn capsule. The objective of this study was to characterize the bacterial communities associated with hoof lesions, which were categorized into 5 stages or disease grade severities, with 0 being unaffected tissue and 4 being sloughed hoof capsule. We also wanted to determine if the etiology of TAHD through morphological changes was dominated by Treponema, as observed in hoof diseases in livestock.ResultsThe bacterial 16S rRNA gene was sequenced from 66 hoof skin biopsy samples representing 5 lesion grades from samples collected by Washington Department of Fish and Wildlife as part of a voluntary hunter program. Analysis of the relative abundance of bacterial sequences showed that lesions were dominated by members of the bacterial phyla Proteobacteria, Firmicutes, Spirochaetes, Bacteroidetes and Actinobacteria. In lesion samples, members of the genus Treponema, Porphyromonas, and Mycoplasma increased with lesion severity. Association analysis indicated frequent identification of Treponema with Porphyromonas, Bacteroides and other anaerobic Gram-positive cocci.ConclusionsThe bacterial 16S rRNA gene sequencing confirmed the presence of Treponema species at all stages of TAHD lesions, treponeme specie-specific PCR and histopathology, indicating that the morphological changes are a continual progression of disease severity with similar bacterial communities. Association and abundance of these other pathogenic genera within lesions may mean synergistic role with Treponema in hoof disease pathogenesis. Characterizing bacteria involved in lesion development, and their persistence during disease progression, provides evidence for science-based management decisions in TAHD infected elk populations.

The Canine Gut Health: The Impact of a New Feed Supplement on Microbiota Composition.

This study aimed to determine the impact of a novel formulation of a supplement composed of the natural ingredients, bromelain, quercetin, and Lentinula edodes, on the gut microbiota of healthy adult dogs. Adult healthy female dogs were administered either a placebo (CTR, n = 15) or the supplement (TRT, n = 15) over 28 days. Stool samples were collected for 16S rRNA sequencing before supplement administration (T0), at completion of supplement administration (T28), and one week after the end of supplement administration (T35) to characterize changes in the gut microbial communities. QIIME was used to determine both alpha- and beta-diversity, and ANCOM-BC was used to identify differences in taxonomic abundances before and after supplementation. We found a significant decrease in overall diversity in the CTR group but no significant differences in overall diversity in the TRT group over time. Furthermore, we found differences in the abundance of several taxa in both the CTR and TRT groups, but differences in the abundance of beneficial bacteria were more pronounced in the TRT group. Specifically, we found increases in the abundance of sequences belonging to the genera Bifidobacterium, Lactobacillus, and Pediococcus at T28 in the TRT group with significant increases in Bifidobacterium and Lactobacillus persisting at T35 when compared to T0. Importantly, members of these genera are considered important for their anti-inflammatory properties, vital for fostering a balanced and robust gut microbiota in dogs. The results of our study show the potential of our supplement to selectively enhance specific beneficial bacterial taxa, offering a targeted approach to modulating the gut microbiome without causing disruptions to the overall equilibrium.

Unprecedented insights into extents of biological responses to physical forcing in an Arctic sub-mesoscale filament by combining high-resolution measurement approaches.

In Fram Strait, we combined underway-sampling using the remote-controlled Automated Filtration System for Marine Microbes (AUTOFIM) with CTD-sampling for eDNA analyses, and with high-resolution optical measurements in an unprecedented approach to determine variability in plankton composition in response to physical forcing in a sub-mesoscale filament. We determined plankton composition and biomass near the surface with a horizontal resolution of ~ 2km, and addressed vertical variability at five selected sites. Inside and near the filament, plankton composition was tightly linked to the hydrological dynamics related to the presence of sea ice. The comprehensive data set indicates that sea-ice melt related stratification near the surface inside the sub-mesoscale filament resulted in increased sequence abundances of sea ice-associated diatoms and zooplankton near the surface. In analogy to the physical data set, the underway eDNA data, complemented with highly sampled phytoplankton pigment data suggest a corridor of 7km along the filament with enhanced photosynthetic biomass and sequence abundances of sea-ice associated plankton. Thus, based on our data we extrapolated an area of 350 km2 in Fram Strait with enhanced plankton abundances, possibly leading to enhanced POC export in an area that is around a magnitude larger than the visible streak of sea-ice.

Assessing aerial biodiversity over Keller Peninsula, King George Island, Maritime Antarctica, using DNA metabarcoding

Abstract Antarctic ice-free areas are dominated by wind-dispersed organisms. However, which organisms arrive and circulate in Antarctica and how remain poorly understood. Due to their proximity to South America and less extreme conditions, the South Shetland Islands are likely to receive higher diaspore numbers. One possible consequence of climate change is that newcomers will be able to colonize ice-free areas, altering community compositions and impacting the native biota. We used DNA metabarcoding to identify non-fungal eukaryotic DNA present in the air that could potentially reach and circulate in Antarctica. Air was sampled near the Brazilian Comandante Ferraz Antarctic Station on King George Island between December 2019 and January 2020. Sequences representing a total of 35 taxa from 10 phyla and 3 kingdoms were assigned: Chromista (Ciliophora, Cercozoa, Haptophyta and Ochrophyta), Plantae (Chlorophyta, Bryophyta and Magnoliophyta) and Animalia (Mollusca, Arthropoda and Chordata). The most diverse group were the plants (26 taxa), followed by Chromista (6 taxa). The most abundant sequences represented the green algae Chlamydomonas nivalis. The two angiosperm sequences represent exotic taxa; Folsomia is also exotic and was recorded only on Deception Island. Metabarcoding revealed the presence of previously undocumented airborne diversity, suggesting that the Antarctic airspora includes propagules of both local and distant origin.

Targeted Sequencing of Human Satellite 2 Repeat Sequences in Plasma cfDNA Reveals Potential Breast Cancer Biomarkers.

Liquid biopsies are revolutionizing the detection and management of malignant diseases. While repetitive DNA sequences, such as LINE-1 and ALU are established in cell-free DNA (cfDNA) research, their clinical applications remain limited. In this study, we explore human satellite 2 (HSATII), a prevalent repeat DNA sequence in plasma that exhibits increased levels in cancer patients, thereby positioning it as a potential pan-cancer biomarker. We employed targeted sequencing and copy number variation (CNV) analysis using two primer pairs to assess the differential abundance of HSATII sequences in the plasma of breast cancer patients compared to healthy individuals. PCR amplicons of HSATII from 10 patients and 10 control subjects were sequenced, generating 151 bp paired-end reads. By constructing a pooled reference dataset, HSATII copy ratios were estimated in the patients. Our analysis revealed several significant CNVs in HSATII, with certain sequences displaying notable gains and losses across all breast cancer patients, suggesting their potential as biomarkers. However, we observed pronounced fragmentation of cfDNA in cancer, leading to the loss of longer PCR amplicons (>180 bp). While not all observed losses can be attributed to fragmentation artifacts, this phenomenon does introduce complexity in interpreting CNV data. Notably, this research marks the first instance of targeted HSATII sequencing in a liquid biopsy context. Our findings lay the groundwork for developing sequencing-based assays to detect differentially represented HSATII sequences, potentially advancing the field of minimally-invasive cancer screening.

Machine learning-based prediction of proteins’ architecture using sequences of amino acids and structural alphabets

In addition to the growth of protein structures generated through wet laboratory experiments and deposited in the PDB repository, AlphaFold predictions have significantly contributed to the creation of a much larger database of protein structures. Annotating such a vast number of structures has become an increasingly challenging task. CATH is widely recognized as one the most common platforms for addressing this challenge, as it classifies proteins based on their structural and evolutionary relationships, offering the scientific community an invaluable resource for uncovering various properties, including functional annotations. While CATH annotation involves – to some extent – human intervention, keeping up with the classification of the rapidly expanding repositories of protein structures has become exceedingly difficult. Therefore, there is a pressing need for a fully automated approach. On the other hand, the abundance of protein sequences stemming from next generation sequencing technologies, lacking structural annotations, presents an additional challenge to the scientific community. Consequently, 'pre-annotating’ protein sequences with structural features, ensuring a high level of precision, could prove highly advantageous. In this paper, after a thorough investigation, we introduce a novel machine-learning model capable of classifying any protein domain, whether it has a known structure or not, into one of the 40 main CATH Architectures. We achieve an F1 Score of 0.92 using only the amino acid sequence and a score of 0.94 using both the sequence of amino acids and the sequence of structural alphabets. Communicated by Ramaswamy H. Sarma

Comparison of microbial communities and nitrite formation in two different beet sugar extraction systems

This study investigated nitrite formation in beet sugar factories, crucial due to tightening European Union directives for contaminants in feed material. Comparing two extraction systems (trough and tower), the trough system exhibited dynamic nitrite formation processes resulting in an average nitrite content of 14.35 mg/kg in raw juice. In the tower system, high nitrite levels and rapid degradation occurred in hot extraction areas, leading to an average nitrite content of 30.89 mg/kg in raw juice during sampling period. Microbial diversity analysis revealed a community shift, with Firmicutes dominating in hot extraction regions. Highly abundant amplicon sequence variants (ASVs) predominantly belonged to the genera Tuberibacillus and Geobacillus in both systems (Tuberibacillus: trough: 73%, tower: 67%; Geobacillus: trough: 41%, tower: 30%). Sequences related to bacteria relevant for nitrite metabolism varied between the two systems. Limosilactobacillus fermentum was more prevalent in the trough extraction system (6% relative abundance in raw juice), than in the tower system (0.5% relative abundance in raw juice). Similarly, Parageobacillus caldoxylolyticus was more abundant in tower extraction, especially in high-temperature zones like the countercurrent mixer (7% relative abundance). These findings provide insights into microbial processes, community structure, and potential strategies for early nitrite reduction in the extraction process.

Light‐Up Sensing Citrate Using a Capture‐Selected DNA Aptamer

AbstractCitrate is a key metabolite and nutrient in humans. Its level is associated with many diseases from tumor growth to bone diseases. Detection of citrate has relied on its high negative charge, metal chelating properties and as an enzyme substrate. In this work, the capture‐selection method is used to isolate DNA aptamers for citrate. After 18 rounds of selection, a highly converged library is obtained and the first two sequences reached 99.6% of the library. Using the most abundant sequence named CA1, thioflavin T fluorescence spectroscopy and isothermal titration calorimetry show dissociation constants of 7.4 and 4.4 µm citrate, respectively. CA1 does not require sodium for binding but requires 1.0 mm magnesium. Among the tested carboxylate molecules, only citrate can bind to the aptamer. A light‐up fluorescence strand displacement biosensor is developed and it can detect citrate in simulated urine with a detection limit of 1.1 µm. This short 42‐nucleotide aptamer can be readily adapted to other types of sensing mechanisms for the detection of citrate.

Highly abundant bacteria in the gut of Triatoma dimidiata (Hemiptera: Reduviidae) can inhibit the growth of Trypanosoma cruzi (Kinetoplastea: Trypanosomatidae).

Chagas disease, caused by the protozoan Trypanosoma cruzi, is a zoonosis primarily found in rural areas of Latin America. It is considered a neglected tropical disease, and Triatoma dimidiata is the main vector of the parasite in Central America. Despite efforts, Chagas disease continues to be a public health concern, and vector control remains a primary tool to reduce transmission. In this study, we tested the hypothesis that highly abundant bacteria in the gut of T. dimidiata inhibit the growth of T. cruzi. To achieve this, bacterial diversity in the gut of T. dimidiata specimens from Costa Rica was characterized by metabarcoding of the 16S rRNA, microbial isolation was performed, and the effect of freeze-dried supernatants of the isolates on T. cruzi was investigated. Metabarcoding showed that the most abundant genera in the gut were Corynebacterium, Tsukamurella, Brevibacterium, and Staphylococcus. Barcoding and sequences comparison confirmed that 8 of the 30 most abundant amplicon sequence variants (ASVs) were isolated, and 2 of them showed an inhibitory effect on the growth of T. cruzi epimastigotes. These bacteria correspond to isolates of Tsukamurella and Brevibacterium, which were respectively the second and sixth most abundant ASVs in the gut of T. dimidiata. Notably, only the isolate of Brevibacterium showed a significant difference in growth inhibition against epimastigotes of both T. cruzi strains tested. These findings suggest that the gut microbiota of T. dimidiata may play an active role in modulating parasite development.

Characterization of the chloroplast genome of Gleditsia species and comparative analysis

The genus Gleditsia has significant medicinal and economic value, but information about the chloroplast genomic characteristics of Gleditsia species has been limited. Using the Illumina sequencing, we assembled and annotated the whole chloroplast genomes of seven Gleditsia species (Gleditsia sinensis, Gleditsia japonica var. delavayi (G. delavayi), G. fera, G. japonica, G. microphylla, Fructus Gleditsiae Abnormalis (Zhū Yá Zào), G. microphylla mutant). The assembled genomes revealed that Gleditsia species have a typical circular tetrad structure, with genome sizes ranging from 162,746 to 170,907 bp. Comparative genomic analysis showed that most (65.8–75.8%) of the abundant simple sequence repeats in Gleditsia and Gymnocladus species were located in the large single copy region. The Gleditsia chloroplast genome prefer T/A-ending codons and avoid C/G-ending codons, positive selection was acting on the rpoA, rpl20, atpB, ndhA and ycf4 genes, most of the chloroplast genes of Gleditsia species underwent purifying selection. Expansion and contraction of the inverted repeat (IR)/single copy (SC) region showed similar patterns within the Gleditsia genus. Polymorphism analysis revealed that coding regions were more conserved than non-coding regions, and the IR region was more conserved than the SC region. Mutational hotspots were mostly found in intergenic regions such as “rps16-trnQ”, “trnT-trnL”, “ndhG-ndhI”, and "rpl32-trnL” in Gleditsia. Phylogenetic analysis showed that G. fera is most closely related to G. sinensis,G. japonica and G. delavayi are relatively closely related. Zhū Yá Zào can be considered a bud mutation of the G. sinensis. The albino phenotype of G. microphylla mutant is not caused by variations in the chloroplast genome, and that the occurrence of the albino phenotype may be due to mutations in chloroplast-related genes involved in splicing or localization functions. This study will help us enhance our exploration of the genetic evolution and geographical origins of the Gleditsia genus.

Monitoring bloom-forming Aphanizomenon using environmental DNA metabarcoding: Method development, validation, and field application

Harmful algal blooms (HABs) have emerged as a critical global environmental and ecological concern. Timely and accurate monitoring of the prevalent bloom-forming genera is crucial for HAB management. Conventional microscope-based methods are time-consuming, labor-intensive, and specialized expertise-dependent, often making them impractical for large-scale surveillance. Molecular methods, such as metabarcoding, provide efficient technical solutions; however, the lack of competent PCR primers and further field validation present obstacles to their wide use. Here, we successfully developed Aphanizomenon-specific primers and validated the application of environmental DNA (eDNA) metabarcoding for field-based monitoring of Aphanizomenon in 37 sites across lentic and lotic freshwater ecosystems in Beijing. The sensitivity and specificity tests of newly developed primers demonstrated high performance - comprehensive recovery of biodiversity in Aphanizomenon communities and high ratios (>95%) of Aphanizomenon sequences in datasets. We observed significant correlations between the sequence abundance derived from eDNA metabarcoding and the total cell density determined through microscopic identification across all the sampling sites, both in the spring (r = 0.8086, p < 0.0001) and summer (r = 0.7902, p < 0.0001), thus validating the utility of eDNA metabarcoding based on the newly developed primers for monitoring in the field. Further, we identified key environmental variables that were primary drivers responsible for the spatiotemporal distribution of Aphanizomenon abundance. These variables included temperature, total nitrogen, and dissolved oxygen in lentic ecosystems, and total phosphorus in lotic ecosystems. The method developed and validated here offers an accurate, efficient, and high-throughput tool for the monitoring of Aphanizomenon blooms in freshwater ecosystems.

The Microbial Community Composition and Nitrogen Cycling Metabolic Potential of an Underground Reservoir in Rizhao, Shandong Province, China

Constructing underground reservoirs has emerged as a crucial strategy to address the shortage of fresh water in Rizhao, Shandong Province, China. However, the water quality, microbial community composition, and biogeochemical cycling of nutrients in underground reservoirs compared to raw water remain unknown. To unveil the characteristics of microbial community structures and their nitrogen cycling metabolic potential in coastal underground reservoirs, we utilized a functional gene array (GeoChip 5.0) in conjunction with high-throughput sequencing of 16S rRNA and 18S rRNA genes. Our findings indicate that the water quality in the underground reservoir exhibits a certain degree of eutrophication compared to raw water, with higher concentrations of TN, TP, NO3−N, NO2−-N, and Chl a, but lower concentrations of DO and NH4+-N. The alpha diversity of bacterial and microeukaryotic communities was significantly lower in the underground reservoir. The bacterial community presented a stronger correlation with environmental factors than the microeukaryotic community. Regarding the relative abundance of bacterial communities, Gammaproteobacteria dominated the bacterial community in raw water, while Gammaproteobacteria and Alphaproteobacteria dominated the bacterial community in underground reservoir water. Additionally, the relative abundance of Nitrospirae was noticeably higher in the underground reservoir water. Moreover, we found significantly higher sequence abundance of the archaea Thaumarchaeota in the underground reservoir. Furthermore, our analysis revealed that, except for the amoA functional gene, which significantly increased the metabolic potential of nitrification, the metabolic potential of other microbial nitrogen functional genes was significantly reduced. This reduction may contribute to the lower concentration of NH4+-N in the underground reservoir. This study provides a comprehensive understanding of the microbial community characteristics and their nitrogen cycling metabolic potential in underground reservoirs. It serves as a valuable reference for water source selection, the formulation of water quality assurance measures, and the construction and management of underground reservoirs for subsequent impounding.

Gut microbiota and inflammatory mediators differentiate IgE mediated and non-IgE mediated cases of cow's milk protein at diagnosis.

Analyze fecal and blood samples at point of diagnosis in IgE mediated cow's milk protein allergy (CMPA) and non-IgE mediated (NIM)-CMPA patients to look for potential new biomarkers. Fourteen patients with IgE mediated CMPA and 13 with NIM-CMPA were recruited in three hospitals in the north of Spain, and were compared with 25 infants from a control group of the same age range. To characterize intestinal microbiota, 16S rDNA gene and internal transcribed spaceramplicons of bifidobacteria were sequenced with Illumina technology. Fatty acids were analyzed by gas chromatography, meanwhile intestinal inflammation markers were quantified by enzyme-linked immunosorbent assayand a multiplex system. Immunological analysis of blood was performed by flow cytometry. The fecal results obtained in the NIM-CMPA group stand out. Among them, a significant reduction in the abundance of Bifidobacteriaceae and Bifidobacterium sequences with respect to controls was observed. Bifidobacterial species were also different, highlighting the lower abundance of Bifidobacterium breve sequences. Fecal calprotectin levels were found to be significantly elevated in relation to IgE mediated patients. Also, a higher excretion of IL-10 and a lower excretion of IL-1ra and platelet derived growth factor-BB was found in NIM-CMPA patients. The differential fecal parameters found in NIM-CMPA patients could be useful in the diagnosis of NIM food allergy to CM proteins.

Insight into planktonic protistan and fungal communities across the nutrient-depleted environment of the South Pacific Subtropical Gyre.

Ocean microorganisms constitute ~70% of the marine biomass, contribute to ~50% of the Earth's primary production, and play a vital role in global biogeochemical cycles. The marine heterotrophic and mixotrophic protistan and fungal communities have often been overlooked mainly due to limitations in morphological species identification. Despite the accumulation of studies on biogeographic patterns observed in microbial communities, our understanding of the abundance and distribution patterns within the microbial community of the largest subtropical gyre, the South Pacific Gyre (SPG), remains incomplete. Here, we investigated the diversity and vertical composition of protistan and fungal communities in the water column of the ultra-oligotrophic SPG. Our results showed apparent differences in protistan community diversity in the photic and aphotic regions. The entire protistan community diversity was significantly affected by temperature, salinity, oxygen, and nutrient concentrations, while the parasitic community diversity was also affected by chlorophyll a concentration. The parasitic protists were assigned to the class Syndiniales accounting for over 98% of the total parasitic protists, exhibiting higher relative sequence abundance along the water depth and displaying consistent patterns among different sampling stations. In contrast to the protistan community, the fungal community along the SPG primarily clustered based on the sampling station and pelagic zones. In particular, our study reveals a significant presence of parasitic protists and functionally diverse fungi in SPG and their potential impact on carbon cycling in the gyre.IMPORTANCEOur findings carry important implications for understanding the distribution patterns of the previously unrecognized occurrence of parasitic protists and functionally diverse fungi in the nutrient-limited South Pacific Gyre. In particular, our study reveals a significant presence of parasitic Syndiniales, predominantly abundant in the upper 300 m of the aphotic zone in the gyre, and a distinct presence of fungal communities in the aphotic zone at the central part of the gyre. These findings strongly suggest that these communities play a substantial role in yet insufficiently described microbial food web. Moreover, our research enhances our understanding of their contribution to the dynamics of the food webs in oligotrophic gyres and is valuable for projecting the ecological consequences of future climate warming.

The 28S rRNA RT-qPCR assay for host depletion evaluation to enhance avian virus detection in Illumina and Nanopore sequencing.

Abundant host and bacterial sequences can obscure the detection of less prevalent viruses in untargeted next-generation sequencing (NGS). Efficient removal of these non-targeted sequences is vital for accurate viral detection. This study presents a novel 28S ribosomal RNA (rRNA) RT-qPCR assay designed to assess the efficiency of avian rRNA depletion before conducting costly NGS for the detection of avian RNA viruses. The comprehensive evaluation of this 28S-test focuses on substituting DNase I with alternative DNases in our established depletion protocols and finetuning essential parameters for reliable host rRNA depletion. To validate the effectiveness of the 28S-test, we compared its performance with NGS results obtained from both Illumina and Nanopore sequencing platforms. This evaluation utilized swab samples from chickens infected with highly pathogenic avian influenza virus, subjected to established and modified depletion protocols. Both methods significantly reduced host rRNA levels, but using the alternative DNase had superior performance. Additionally, utilizing the 28S-test, we explored cost- and time-effective strategies, such as reduced probe concentrations and other alternative DNase usage, assessed the impact of filtration pre-treatment, and evaluated various experimental parameters to further optimize the depletion protocol. Our findings underscore the value of the 28S-test in optimizing depletion methods for advancing improvements in avian disease research through NGS.

ADH-Enhancer: an attention-based deep hybrid framework for enhancer identification and strength prediction.

Enhancers play an important role in the process of gene expression regulation. In DNA sequence abundance or absence of enhancers and irregularities in the strength of enhancers affects gene expression process that leads to the initiation and propagation of diverse types of genetic diseases such as hemophilia, bladder cancer, diabetes and congenital disorders. Enhancer identification and strength prediction through experimental approaches is expensive, time-consuming and error-prone. To accelerate and expedite the research related to enhancers identification and strength prediction, around 19 computational frameworks have been proposed. These frameworks used machine and deep learning methods that take raw DNA sequences and predict enhancer's presence and strength. However, these frameworks still lack in performance and are not useful in real time analysis. This paper presents a novel deep learning framework that uses language modeling strategies for transforming DNA sequences into statistical feature space. It applies transfer learning by training a language model in an unsupervised fashion by predicting a group of nucleotides also known as k-mers based on the context of existing k-mers in a sequence. At the classification stage, it presents a novel classifier that reaps the benefits of two different architectures: convolutional neural network and attention mechanism. The proposed framework is evaluated over the enhancer identification benchmark dataset where it outperforms the existing best-performing framework by 5%, and 9% in terms of accuracy and MCC. Similarly, when evaluated over the enhancer strength prediction benchmark dataset, it outperforms the existing best-performing framework by 4%, and 7% in terms of accuracy and MCC.