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Zheng, L.

Publications and source records attributed to Zheng, L..

At least 199 records · Page 11Linked to original sources

Measuring aptamer folding energy using a molecular clamp

Folding energy offers a useful metric for characterizing the stability and function of aptamers. However, experimentally measuring the folding energy is challenging and there is currently no general technique to measure this parameter directly. In this work, we present a simple approach for measuring aptamer folding energy. First, the aptamer is stretched under equilibrium conditions with a double-stranded DNA "molecular clamp" that is coupled to the aptamer ends. We then measure the total internal energy of stressed DNA molecules using time-lapse gel electrophoresis and compare the folding and unfolding behavior of molecular clamp-stressed molecules that incorporate either the aptamer or unstructured random single-stranded DNA in order to derive the aptamer folding energy. Using this approach, we measured a folding energy of 10.40 kJ/mol for the HD22 thrombin aptamer, which is consistent with other predictions and estimates. We also analyzed a simple hairpin structure, generating a folding energy result of 9.05 kJ/mol, consistent with the value predicted by computational models (9.24 kJ/mol). We believe our strategy offers an accessible and generalizable approach for obtaining such measurements with virtually any aptamer.

biophysics↗

Contrasting population genetics of cattle- and buffalo- derived Theileria annulata causing tropical theileriosis

The present study was designed to improve understanding of Theileria annulata in sympatric water buffalo and cattle in the Punjab province of Pakistan. The prevalence of tropical theileriosis is high, buparvaquone resistance is widespread, and vaccine protection is poor in the field. Better understanding is, therefore, needed of the factors that influence the genetics of T. annulata populations both within its hosts and in its overall populations. Here we utilise a panel of six satellites and a mitochondrial cytochrome b marker to explore the multiplicity of T. annulata infection and patterns of emergence and spread of different parasite genotypes. Parasite materials were collected from infected animals in defined regions, where water buffalo and cattle are kept together. Our results show that T. annulata is genetically more diverse in cattle- than in water buffalo-derived populations (the mean numbers of unique satellite alleles were 13.3 and 1.8 and numbers of unique cytochrome b locus alleles were 65 and 27 in cattle- and water buffalo-derived populations, respectively). The data show a high level of genetic diversity among the individual host-derived populations (the overall heterozygosity (He) indices were 0.912 and 0.931 in cattle, and 0.874 and 0.861 in buffalo, based on satellite and cytochrome b loci, respectively). When considered in the context of high parasite transmission rates and frequent animal movements between different regions, the predominance of multiple T. annulata genotypes, with multiple introductions of infection in the hosts from which the parasite populations were derived, may have practical implications for the spread of parasite genetic adaptations; such as those conferring vaccine cross-protection against different strains affecting cattle and buffalo, or resistance to antiprotozoal drugs.

genetics↗

Contrast-Enhanced, Molecular Imaging of Vascular Inflammation in the Mouse Model by Simultaneous PET/MRI

Despite advances in diagnosis and management, cardiovascular diseases (CVDs) remain the leading cause of death in the US. Atherosclerosis is the most common form of CVD and the vulnerability of atherosclerotic plaques to rupture is a primary determinant for risk of catastrophic ischemic events. Current imaging of atherosclerotic disease focuses on assessing plaque size and the degree of luminal stenosis, which are not good predictors of plaque stability. Functional methods to identify biomarkers of inflammation in plaques could facilitate assessment of plaque instability to allow early intervention. In this study, we validate the use of a purpose-built, magnetic resonance imaging (MRI)-compatible positron emission tomography (PET) insert for multimodal, molecular imaging of vulnerable plaques in mice. We illustrate the application of PET to screen for inflamed regions to guide the application of MRI. Molecular MRI visualizes regions of vascular inflammation and is coupled with anatomical MRI to generate detailed maps of the inflammatory marker within the context of an individual vessel. As a testbed for this imaging methodology, we developed a multimodal, iron oxide nanoparticle (NP) targeting vascular cell adhesion molecule-1 (VCAM-1) for simultaneous PET/MRI of vascular inflammation performed on a mouse carotid ligation model. In vitro cell studies confirmed that the NPs are not cytotoxic to liver cells. In vivo simultaneous PET/MRI imaging identified regions of inflammation. Three-dimensional rendering of the MRI data facilitated high-resolution visualization of patterns of inflammation along the injured vessel. Histology validated the co-localization of the NPs with VCAM-1 expression at sites of induced inflammation. The results of this work validate the utility of the simultaneous PET/MR insert as a research tool for small animals and lays groundwork to further advance the potential clinical utility of integrated imaging systems.

bioengineering↗

Dual oxidase gene Duox and Toll-like receptor 3 gene TLR3 in the Toll pathway suppress zoonotic pathogens through regulating the intestinal bacterial community homeostasis in Hermetia illucens L.

Black soldier fly (BSF; Hermetia illucens L.) larvae can convert fresh pig manure into protein and fat-rich biomass, which can then be used as livestock feed. Currently, it is the only insect approved for such purposes in Europe, Canada, and the USA. Pig manure is rich in zoonotic pathogens (e.g., Staphylococcus aureus and Salmonella spp.). BSF larvae inhibit these zoonotic pathogens; however, the mechanism is unclear. We employed RNAi, qRT-PCR, and Illumina MiSeq bacterial 16S rDNA high-throughput sequencing molecular techniques to study the interaction between the two immune genes (Duoxin Duox-reactive oxygen species [ROS] immune system and TLR3 in the Toll signaling pathway) and zoonotic pathogens to determine the mechanisms resulting in pathogen suppression. Results indicated that Bsf Duox-TLR3 RNAi increased bacterial load but decreased the relative abundance of Providenciaand Dysgonomonasintestinal symbionts. Concurrently, Bsf Duox-TLR3 RNAi inactivated the NF-{kappa} B signaling pathway, downregulated the expression of antimicrobial peptides, and diminished inhibitory effects on zoonotic pathogen. The resulting dysbiosis stimulated an immune response by activating BsfDuox and promoting ROS, which regulated the composition and structure of the gut bacterial community. Thus, BsfDuox and BsfTLR3 are important factors in regulating the gut key bacteria Providenciaand Dysgonomonas homeostasis while inhibiting target zoonotic pathogens.

microbiology↗

Interactions of encoding and decoding problems to understand motor control

Learning a map from movement to neural data (Encoding Problem) and vice versa (Decoding Problem) are crucial to understanding motor control. A principled encoding model that understands underlying neural dynamics can help better solve the decoding problem. Here, we develop a new generative encoding model leveraging deep learning that autonomously captures neural dynamics. After training, the model can synthesize spike trains given any observed kinematics, under the guidance of the learned neural dynamics. When neural data from other sessions or subjects are limited, synthesized spike trains can improve cross-session and cross-subject decoding performance of a Brain Computer Interface decoder. For cross-subject, even with ample data for both subjects, neural dynamics learned from a previous subject can transfer useful knowledge that improves the best achievable decoding performance for the new subject. The approach is general and fully data-driven, and hence could apply to neuroscience encoding and decoding problems beyond motor control.

neuroscience↗

OpenCRAVAT, an open source collaborative platform for the annotation of human genetic variation

PURPOSEThe modern researcher is confronted with hundreds of published methods to interpret genetic variants. There are databases of genes and variants, phenotype-genotype relationships, algorithms that score and rank genes, and in silico variant effect prediction tools. Because variant prioritization is a multi-factorial problem, a welcome development in the field has been the emergence of decision support frameworks, which make it easier to integrate multiple resources in an interactive environment. Current decision support frameworks are typically limited by closed proprietary architectures, access to a restricted set of tools, lack of customizability, web dependencies that expose protected data, or limited scalability.\n\nMETHODSWe present OpenCRAVAT, a new open source, scalable decision support system for variant and gene prioritization. We have designed the resource catalog to be open and modular to maximize community and developer involvement, and as a result the catalog is being actively developed and growing every month. Resources made available via the store are well-suited for analysis of cancer, as well as Mendelian and complex diseases.\n\nRESULTSOpenCRAVAT offers both command line utility and dynamic GUI, allowing users to install with a single command, easily download tools from an extensive resource catalog, create customized pipelines, and explore results in a richly detailed viewing environment. We present several case studies to illustrate the design of custom workflows to prioritize genes and variants.\n\nCONCLUSIONOpenCRAVAT is distinguished from similar tools by its capabilities to access and integrate an unprecedented amount of diverse data resources and computational prediction methods, which span germline, somatic, common, rare, coding and non-coding variants. OpenCRAVAT is freely available at https://opencravat.org

bioinformatics↗

High-throughput prediction of MHC Class I and Class II neoantigens with MHCnuggets

Computational prediction of binding between neoantigen peptides and major histocompatibility complex (MHC) proteins is an emerging biomarker for predicting patient response to cancer immunotherapy. Current neoantigen predictors focus on in silico estimation of MHC binding affinity and are limited by low positive predictive value for actual peptide presentation, inadequate support for rare MHC alleles and poor scalability to high-throughput data sets. To address these limitations, we developed MHCnuggets, a deep neural network method to predict peptide-MHC binding. MHCnuggets is the only method to handle binding prediction for common or rare alleles of MHC Class I or II, with a single neural network architecture. Using a long short-term memory network (LSTM), MHCnuggets accepts peptides of variable length and is capable of faster performance than other methods. When compared to methods that integrate binding affinity and HLAp data from mass spectrometry, MHCnuggets yields a fourfold increase in positive predictive value on independent MHC-bound peptide (HLAp) data. We applied MHCnuggets to 26 cancer types in TCGA, processing 26.3 million allele-peptide comparisons in under 2.3 hours, yielding 101,326 unique candidate immunogenic missense mutations (IMMs). Predicted-IMM hotspots occurred in 38 genes, including 24 driver genes. Predicted-IMM load was significantly associated with increased immune cell infiltration (p<2e-16) including CD8+ T cells. Notably, only 0.16% of predicted immunogenic missense mutations were observed in >2 patients, with 61.7% of these derived from driver mutations. Our results provide a new method for neoantigen prediction with high performance characteristics and demonstrate its utility in large data sets across human cancers.\n\nSynopsisWe developed a new in silico predictor of Major Histocompatibility Complex (MHC) ligand binding and demonstrated its utility to assess potential neoantigens and immunogenic missense mutations (IMMs) in 6613 TCGA patients.

immunology↗

Neck Musculoskeletal Model Generation through Anthropometric Scaling

A new methodology was developed to quickly generate whole body models with detailed neck musculoskeletal architecture that are properly scaled in terms of anthropometry and muscle strength. This method was implemented in an anthropometry model generation software that allows users to interactively generate any new male or female musculoskeletal models with adjustment of anthropometric parameters (such as height, weight, neck circumference, and neck length) without the need of subject-specific motion capture or medical images. 50th percentile male and female models were developed based on the 2012 US Army Anthropometric Survey (ANSUR II) database and optimized with a novel bilevel optimization method to have strengths comparable to experimentally measured values in the literature. Other percentile models (ranging from the 1st to 99th percentile) were generated based on anthropometric scaling of the 50th percentile models and compared. The resultant models are reasonably accurate in terms of both musculoskeletal geometry and neck strength, demonstrating the effectiveness of the developed methodology for interactive neck model generation with anthropometric scaling.

bioengineering↗

Vegetative Cell and Spore Proteomes of Peptoclostridium difficile show finite differences and reveal potential biomarkers.

Clostridioides difficile-associated infection (CDI) is a health-care-associated infection mainly transmitted via highly resistant endospores from one person to the other. In vivo, the spores need to germinate in to cells prior to establishing an infection. Bile acids and glycine, both available in sufficient amounts inside the human host intestinal tract, serve as efficient germinants for the spores. It is therefore, for better understanding of Clostridioides difficile virulence, crucial to study both the cell and spore states with respect to their genetic, metabolic and proteomic composition. In the present study, mass spectrometric relative protein quantification, based on the 14N/15N peptide isotopic ratios, has led to quantification of over 700 proteins from combined spore and cell samples. The analysis has revealed that the proteome turnover between a vegetative cell and a spore for this organism is moderate. Additionally, specific cell and spore surface proteins, vegetative cell proteins CD1228, CD3301 and spore proteins CD2487, CD2434 and CD0684 are identified as potential protein markers for C. difficile infection.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC=\"FIGDIR/small/598045v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (18K):\norg.highwire.dtl.DTLVardef@c5969aorg.highwire.dtl.DTLVardef@228704org.highwire.dtl.DTLVardef@ce49f1org.highwire.dtl.DTLVardef@158928e_HPS_FORMAT_FIGEXP M_FIG Abstract graphic For Table of Contents Only\n\nC_FIG

microbiology↗

Identification of DNA motifs that regulate DNA methylation

DNA methylation is an important epigenetic mark but how its locus-specificity is decided in relation to DNA sequence is not fully understood. Here, we have analyzed 34 diverse whole-genome bisulfite sequencing datasets in human and identified 313 motifs, including 92 and 221 associated with methylation (methylation motifs, MMs) and unmethylation (unmethylation motifs, UMs), respectively. The functionality of these motifs is supported by multiple lines of evidences. First, the methylation levels at the MM and UM motifs are respectively higher and lower than the genomic background. Second, these motifs are enriched at the binding sites of methylation modifying enzymes including DNMT3A and TET1, indicating their possible roles of recruiting these enzymes. Third, these motifs significantly overlap with SNPs associated with gene expression and those with DNA methylation. Fourth, disruption of these motifs by SNPs is associated with significantly altered methylation level of the CpGs in the neighbor regions. Furthermore, these motifs together with somatic SNPs are predictive of cancer subtypes and patient survival. We revealed some of these motifs were also associated with histone modifications, suggesting possible interplay between the two types of epigenetic modifications. We also found some motifs form feed forward loops to contribute to DNA methylation dynamics.

bioinformatics↗

Ca2+-activated K+ channels reduce network excitability, improving adaptability and energetics for transmitting and perceiving sensory information

Ca2+-activated K+ channels (BK and SK) are ubiquitous in synaptic circuits, but their role in network adaptation and sensory perception remains largely unknown. Using electrophysiological and behavioral assays and biophysical modelling, we discover how visual information transfer in mutants lacking the BK channel (dSlo-), SK channel (dSK-) or both (dSK-;;dSlo-) is shaped in the Drosophila R1-R6 photoreceptor-LMC circuits (R-LMC-R system) through synaptic feedforward-feedback interactions and reduced R1-R6 Shaker and Shab K+ conductances. This homeostatic compensation is specific for each mutant, leading to distinctive adaptive dynamics. We show how these dynamics inescapably increase the energy cost of information and distort the mutants motion perception, determining the true price and limits of homeostatic compensation in an in vivo genetic animal model. These results reveal why Ca2+-activated K+ channels reduce network excitability (energetics), improving neural adaptability for transmitting and perceiving sensory information.\n\nHighlightsO_LIHomeostatic plasticity in Drosophila dSlo-, dSK- and dSK-;;dSlo- null-mutants retains R1-R6 photoreceptors light information sampling while reducing other K+-conductances\nC_LIO_LIAs mutant R-LMC-R circuits rebalance synaptic loads homeostatically, R1-R6s become more depolarized, with dSK- and dSK-;;dSlo- responding faster and dSlo- slower, whilst LMC outputs oscillate, with dSK- responding faster and dSK-;;dSlo- and dSlo- slower than wild-type\nC_LIO_LIHomeostatic compensation in the mutant circuits impedes adaptation, increases the energy cost of visual information and distorts optomotor behavior\nC_LIO_LIHence, Ca2+-activated K+ channels improve adaptability and energetics for transmitting and perceiving sensory information\nC_LI

neuroscience↗

Changes in pregnancy-related serum biomarkers early in gestation are associated with later development of preeclampsia

BackgroundPlacental protein expression plays a crucial biological role during normal and complicated pregnancies. We hypothesized that: (1) circulating pregnancy-associated, placenta-related protein levels throughout gestation reflect the uncomplicated, full-term temporal progression of human gestation, and effectively estimates gestational ages (GAs); (2) pregnancies with underlying placental pathology, such as preeclampsia (PE), are associated with disruptions in this GA estimation in early gestation; (3) malfunctions of this GA estimation can be employed to identify impending PE. In addition, to explore the underlying biology and PE etiology, we set to compare protein gestational patterns of human and mouse, using pregnant heme oxygenase-1 (HO-1) heterozygote (Het) mice, a mouse model reflecting PE-like symptoms.\n\nMethodsSerum levels of circulating placenta-related proteins - leptin (LEP), chorionic somatomammotropin hormone like 1 (CSHL1), elabela (ELA), activin A, soluble fms-like tyrosine kinase 1 (sFlt-1), and placental growth factor (PlGF)- were quantified by ELISA in blood serially collected throughout human pregnancies (20 normal subjects with 66 samples, and 20 PE subjects with 61 samples). Linear multivariate analysis of the targeted serological protein levels was performed to estimate the normal GA. Logarithmic transformed mean-squared errors of GA estimations were used to identify impending PE. Then the human gestational protein patterns were compared to those in the pregnant HO-1 mice.\n\nResultsAn elastic net (EN)-based gestational dating model was developed (R2 = 0.76) and validated (R2 = 0.61) using the serum levels of the 6 proteins at various GAs from women with normal uncomplicated pregnancies (n = 10 for training and n = 6 for validation). In pregnancies complicated by PE (n = 14), the EN model was not (R2 = -0.17) associated with GA at sampling in PE. Statistically significant deviations from the normal GA EN model estimations were observed in PE-associated pregnancies between GAs of 16-30 weeks (P = 0.01). The EN model developed with 5 proteins (ELA excluded due to the lack of robustness of the mouse ELA essay) performed similarly on normal human (R2 = 0.68) and WT mouse (R2 = 0.85) pregnancies. Disruptions of this model were observed in both human PE-associated (human: R2 = 0.27) and mouse HO-1 Het (mouse: R2 = 0.30) pregnancies. LEP out performed sFlt-1 and PlGF in differentiating impending PE at early human and late mouse gestations.\n\nConclusionsAs revealed in both human and mouse GA EN analyses, temporal serological placenta-related protein patterns are tightly regulated throughout normal human pregnancies and can be significantly disrupted in pathologic PE states. LEP changes earlier during gestation than the well-established late GA PE biomarkers (sFlt-1 and PlGF). Our HO-1 Het mouse analysis provides direct evidence of the causative action of HO-1 deficiency in LEP upregulation in a PE-like murine model. Therefore, longitudinal analyses of pregnancy-related protein patterns in sera, may not only help in the exploration of underlying PE pathophysiology but also provide better clinical utility in PE assessment.

molecular biology↗

Crystal Structure of a Natural Light-Gated Anion Channelrhodopsin

The anion channelrhodopsin GtACR1 from the alga Guillardia theta is a potent neuron-inhibiting optogenetics tool. Presented here, its X-ray structure at 2.9 [A] reveals a tunnel traversing the protein from its extracellular surface to a large cytoplasmic cavity. The tunnel is lined primarily by small polar and aliphatic residues essential for anion conductance. A disulfide-immobilized extracellular cap facilitates channel closing and the ion path is blocked mid-membrane by its photoactive retinylidene chromophore and further by a cytoplasmic side constriction. The structure also reveals a novel photoactive site configuration that maintains the retinylidene Schiff base protonated when the channel is open. These findings suggest a new channelrhodopsin mechanism, in which the Schiff base not only controls gating, but also serves as a direct mediator for anion flux.

biochemistry↗

RAD51 AND MITOTIC FUNCTION OF MUS81 ARE ESSENTIAL FOR RECOVERY FROM LOW-DOSE OF CAMPTOTHECIN IN THE ABSENCE OF THE WRN EXONUCLEASE

Stabilisation of the stalled replication fork is crucial to prevent excessive fork reversal or degradation, which can undermine genome integrity. The WRN protein is a human RecQ helicase that participates in the processing and recovery of perturbed replication forks. WRN is unique among the other human RecQ family members to possess exonuclease activity. However, the biological role of the WRN exonuclease is poorly defined, and little is known about an involvement in the response to perturbed replication. Recently, the WRN exonuclease has been linked to protection of stalled forks from MRE11-dependent degradation in response to clinically-relevant nanomolar doses of the Topoisomerase I inhibitor camptothecin. Alternative processing of perturbed forks has been associated to chemoresistance of BRCA-deficient cancer cells, thus, we used WRN exonuclease-deficiency as a model to investigate the fate of perturbed replication forks undergoing degradation, but in a BRCA wild-type condition. We find that, upon nanomolar doses of camptothecin, loss of WRN exonuclease stimulates fork inactivation and accumulation of parental gaps, which engages RAD51. Such alternative mechanism affects reinforcement of CHK1 phosphorylation and causes persistence of RAD51 during recovery from treatment. Notably, in WRN exonuclease-deficient cells, persistence of RAD51 correlates with elevated mitotic phosphorylation of MUS81 at Serine 87, which is essential to avoid accumulation of mitotic abnormalities. Altogether, these findings indicate that aberrant fork degradation, in the presence of a wild-type RAD51 axis, stimulates RAD51-mediated post-replicative repair and engagement of the MUS81 complex to limit genome instability and cell death.\n\nAUTHOR SUMMARYCorrect progression of the molecular machine copying the chromosomes is threatened by multiple causes that induce its delay or arrest. Once the replication machinery is arrested, the cell needs to stabilise it to prevent DNA damage. Many proteins contribute to this task and the Werners syndrome protein, WRN, is one of them.\n\nDefining what happens to replication machineries when they are blocked is highly relevant. Indeed, destabilised replication machineries may form upon treatment with anticancer drugs and influence the efficacy of some of them in specific genetic backgrounds. We used cells that lack one of the two enzymatic functions of WRN, the exonuclease activity, to investigate the fate of destabilised replication machineries. Our data show that they are handled by a repair pathway normally involved in fixing DNA breaks but, in this case, recruited to deal with regions of the genome that are left unreplicated after their destabilisation. This alternative mechanism involves a protein, RAD51, which tries to copy DNA from the sister chromosome. In so doing, however, RAD51 produces a lot of DNA interlinking that requires upregulation of a complex, called MUS81/EME1, which resolves this interlinking prior cell division and prevents accumulation of mitotic defects and cell death.

cell biology↗

Genome-wide identification of functional tRNA-derived fragments in Senescence-accelerated mouse prone 8 brain

tRNA-derived fragments (tRFs) have been linked previously to the development of various diseases, such as cancer and viral infection. However, tRFs seem also related to brain aging and related diseases, especially Alzheimer and Parkinson disease. RNA sequencing, a state-of-the-art technology, has allowed for investigation of tRFs in this field. In this study, we investigated the changes of tRFs in the brains of a senescence-accelerated mouse model, senescence-accelerated mouse prone 8 (SAMP8), that show age-dependent deficits in learning and memory; and a control model, senescence-accelerated mouse resistant 1 (SAMR1), with normal aging, both at 7 months of age. A total of 570 tRF transcripts were discovered. Among these transcripts, 8, including 3 upregulated and 5 downregulated transcripts, were differentially expressed in the SAMP8 mice. Then, we obtained 110 potential target genes in a miRNA-like pattern. GO survey implicated these target genes in the function of various aspects, e.g. postsynaptic density (GO: 0014069). Furthermore, we assessed in detail those tRFs whose miRNA-like pattern was most likely to affect the progression of either Alzheimer and Parkinson disease, such as AS-tDR-011775 acting on Mobp and Park2. In fact, we found the tRFs to be involved in the regulation of gene expression by means other than the miRNA-like pattern. Therefore, these 8 dysregulated tRFs may hold consequences far into the future and can be attractive biomarkers and valid targets. In brief, our study is the first to provide a comprehensive analysis on tRFs in SAMP8 mouse brain, and this breakthrough identified promising new targets for preventing the age-related changes of brain and the therapeutic intervention of Alzheimers and Parkinsons.

neuroscience↗

SSCC: a computational framework for rapid and accurate clustering of large-scale single cell RNA-seq data

Clustering is a prevalent analytical means to analyze single cell RNA sequencing data but the rapidly expanding data volume can make this process computational challenging. New methods for both accurate and efficient clustering are of pressing needs. Here we proposed a new clustering framework based on random projection and feature construction for large scale single-cell RNA sequencing data, which greatly improves clustering accuracy, robustness and computational efficacy for various state-of-the-art algorithms benchmarked on multiple real datasets. On a dataset with 68,578 human blood cells, our method reached 20% improvements for clustering accuracy and 50-fold acceleration but only consumed 66% memory usage compared to the widely-used software package SC3. Compared to k-means, the accuracy improvement can reach 3-fold depending on the concrete dataset. An R implementation of the framework is available from https://github.com/Japrin/sscClust.

bioinformatics↗

Microbial Community Structure and Diversity of Shrimp Paste at Different Fermentation Stages

High-throughput sequencing was used to reveal the highly diverse bacterial populations in shrimp paste at different fermentation stages. We studied three stages of fermentation and obtained 448,916 reads. Using this approach, we revealed the presence of 30 phyla, 55 classes, 86 orders, 206 families and 695 genera of bacteria in the shrimp paste. Shrimp paste in fermentation metaphase had a more diverse microbiota than that in fermentation prophase and fermentation anaphase. Diversity appeared greatest in fermentation anaphase. The four dominant phyla were Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes. The most common genera were Psychrobacter, Halomonas, Bacillus, Alteribacillus, and Lactococcus. Their content varied at different stages of fermentation. All the microbiome presented a variety of changes in the microbial diversity of shrimp paste.\n\nImportanceMost research on the microbial diversity of shrimp paste has focused on the shrimp culture environment, or the chemical composition and sensory attributes of the paste. Little research has been conducted on the microbial diversity and composition of shrimp paste. The relationship between microbes and the flavor and quality of shrimp paste has thus been unknown. We therefore analyzed the microbial composition and variation of shrimp paste at different stages of fermentation. The dominant bacteria in fermentation prophase, metaphase, and anaphase were identified. Our preliminary findings give some insight into which microbes contribute to the flavor of shrimp paste and suggest how to improve its flavor. In addition, our findings are relevant to optimizing the production of shrimp paste and guaranteeing its quality and safety.

microbiology↗

Effect of eco-remediation and microbial community using multilayer solar planted floating island (MS-PFI) in the drainage channel

A multilayer solar planted floating island (MS-PFI) planted with Eichhornia crassipes are potential alternatives to traditional PFI. The highest removal rates of suspended solids, total nitrogen, total phosphorus, ammonia nitrogen and chemical oxygen demand was 86%, 75%, 80%, 95% and 84%, respectively. Proteobacteria (average 43.4% of total sequences) and Actinobacteria (19.9%) were the dominant phyla. Numerous genus had obvious differences between influent and effluent water, for instance, 13, 12 and 7 % in effluent water were assigned to the hgcl_clade, Norank_c_Cyanobacteria, and Rhizorhapis, while their relative abundances were decreased to 5, 3 and 0 %. In contrast, a distinct increase among Flavobacterium (10%), Limnohabitans (7%), Alpinimonas (4%), norank_p_Saccharibacteria (4%), Erwinia (3%) after MS-PFI treatment. MS-PFI brings various bacteria involved in contaminant degradation and nutrient removal in biological wastewater treatment systems. An amount of {yen} 1,843 was totally inputted to construct floating bed, which was rarely needed operation and maintenance costs.\n\nImportanceIn-situ micro-polluted water ecological remediation, microorganisms and plants are effective to improve environmental quality and provide essential ecosystem services. Recently, we invent a new multilayer solar with an excellent pollutant removal efficiency. Microbes can decompose or mineralize organic matter effectively, also provide food for aquatic animals and increase nutrients or substances for plants, it is an important part of biogeochemical cycles and energy flows in aquatic ecological systems. However, few study explain the bacteria diversity and its responses between influent and effluent water in a planted floating island. The significance of our study is in identifying-in greater detail-the responses of bacteria in the new MS-PFI. This will greatly enhance our knowledge of bacteria communities, and can be widely used in micro-polluted water remediation.

bioengineering↗