Biology subjects

Zhou, G.

Publications and source records attributed to Zhou, G..

At least 127 records · Page 7Linked to original sources

bioRxiv2020

Selective germline genome edited pigs and their long immune tolerance in Non Human Primates

Organ transplantation is the only curative treatment for patients with terminal organ failure, however, there is a worldwide organ shortage. Genetically modified pig organs and tissues have become an attractive and practical alternative solution for the severe organ shortage, which has been made possible by significant progress in xenotransplantation in recent years. The past several decades witnessed an expanding list of genetically engineered pigs due to technology advancements, however, the necessary combination of genetic modifications in pig for human organ xenotransplantation has not been determined. In the current study, we created a selective germline genome edited pig (SGGEP). The first triple xenoantigens (GGTA, B4GAL, and CAMH) knockout somatic cells were generated to serve as a prototype cells and then human proteins were expressed in the xenoantigen knockout cells, which include human complement system negative regulatory proteins (CD46, CD55, and CD59); human coagulation system negative regulatory proteins thrombomodulin (THBD); tissue factor pathway inhibitor (TFPI); CD39; macrophage negative regulatory proteins (human CD47); and natural killer cell negative regulatory human HLA-E. After the successful establishment of SGGEP by the nuclear tranfer, we engrafted SGGEP skin to NHP, up to 25 days graft survival without immunosuppressive drugs was observed. Because a pig skin graft does not impact the success of a subsequent allograft or autograft or vice versa, thus our SGGEP could have a great potential for clinical value to save severe and large area burn patients and the other human organ failure. Therefore, this combination of specific gene modifications is a major milestone and provides proof of concept to initiate investigator-initiated clinical trials (IITs) in severe burn patients with defined processes and governance measures in place and the other clinical application.

synthetic biology↗

bioRxiv2019

Mutation effect estimation on protein-protein interactions using deep contextualized representation learning

The functional impact of protein mutations is reflected on the alteration of conformation and thermodynamics of protein-protein interactions (PPIs). Quantifying the changes of two interacting proteins upon mutations are commonly carried out by computational approaches. Hence, extensive research efforts have been put to the extraction of energetic or structural features on proteins, followed by statistical learning methods to estimate the effects of mutations to PPI properties. Nonetheless, such features require extensive human labors and expert knowledge to obtain, and have limited abilities to reflect point mutations. We present an end-to-end deep learning framework, MuPIPR, to estimate the effects of mutations on PPIs. MuPIPR incorporates a contextualized representation mechanism of amino acids to propagate the effects of a point mutation to surrounding amino acid representations, therefore amplifying the subtle change in a long protein sequence. On top of that, MuPIPR leverages a Siamese residual recurrent convolutional neural encoder to encode a wildtype protein pair and its mutation pair. Multiple-layer perceptron regressors are applied to the protein pair representations to predict the quantifiable changes of PPI properties upon mutations. Experimental evaluations show that MuPIPR outperforms various state-of-the-art systems on the change of binding affinity prediction and the buried surface area prediction. The software implementation is available at https://github.com/guangyu-zhou/MuPIPR

bioinformatics↗

bioRxiv2019

Towards Practical and Robust DNA-based Data Archiving by Codec System Named ‘Yin-Yang’

DNA is a promising data storage medium due to its remarkable durability and space-efficient storage. Early bit-to-base transcoding schemes have primarily pursued information density, at the expense however of introducing biocompatibility challenges or at the risk of decoding failure. Here, we propose a robust transcoding algorithm named the "Yin-Yang Codec" (YYC), using two rules to encode two binary bits into one nucleotide, to generate DNA sequences highly compatible with synthesis and sequencing technologies. We encoded two representative file formats and stored them in vitro as 200-nt oligo pools and in vivo as an ~54-kb DNA fragment in yeast cells. Sequencing results show that YYC exhibits high robustness and reliability for a wide variety of data types, with an average recovery rate of 99.94% at 104 molecule copies and an achieved recovery rate of 87.53% at 100 copies. In addition, the in vivo storage demonstration achieved for the first time an experimentally measured physical information density of 198.8 EB per gram of DNA (44% of the theoretical maximum for DNA).

synthetic biology↗

bioRxiv2019

Resting behaviour of malaria vectors in a highland and a lowland site of western Kenya: Implication on malaria vector control measures

BackgroundUnderstanding the interactions between increased insecticide resistance in field malaria vector populations and the subsequent resting behaviour patterns is important for planning adequate vector control measures in a specific context and sustaining the current vector interventions. The aim of this study was to investigate the resting behavior, host preference and infection with Plasmodium falciparum sporozoites by malaria vectors in different ecological settings of western Kenya with different levels of insecticide resistance. MethodsIndoor and outdoor resting Anopheline mosquitoes were sampled during the dry and rainy seasons in Kisian (lowland site) and Bungoma (highland site), both in western Kenya. WHO tube bioassay was used to determine levels of phenotypic resistance of first generation offspring (F1 progeny) of malaria vectors resting indoors and outdoors to deltamethrin. PCR-based molecular diagnostics were used for mosquito speciation, genotype for resistance mutations and to determine specific host blood meal origins. Enzyme-linked Immunosorbent Assay (ELISA) was used to determine mosquito sporozoite infections. ResultsOverall, 3,566 female Anopheles mosquitoes were collected with Anopheles gambiae s.l [In Bungoma, An. gambiae s.s (90.9%), An arabiensis (7.6%) and in Kisian, An. gambiae s.s (38.9%), An. arabiensis (60.2%)] being the most abundant species (74.7%) followed by An. funestus s.l (25.3%). The majority of An. gambiae s.l (85.4 and 58%) and An. funestus (96.6 and 91.1%) were caught resting indoors in Bungoma and Kisian respectively.Vgsc-1014S was observed at a slightly higher frequency in An. gambiae s.s hereafter(An. gambiae) resting indoor than outdoor (89.7 vs 84.6% and 71.5 vs 61.1%) in Bungoma and Kisian respectively. For An. arabiensis, Vgsc-1014S was 18.2% indoor and outdoor (17.9%) in Kisian. In Bungoma, the Vgsc-1014S was only detected in An. arabiensis resting indoors with a frequency of 10%. The Vgsc-1014F mutation was only present in An. gambiae resting indoors from both sites, but at very low frequencies in Kisian compared to Bungoma (0.8 and 9.2% respectively. In Bungoma, the sporozoite rates for An. funestus, An. gambiae, and An. arabiensis resting indoors were 10.9, 7.6 and 3.4 % respectively. For outdoor resting, An. gambiae and An. arabiensis in Bungoma, the sporozoite rates were 4.7 and 2.9 % respectively.Overall, in Bungoma, the sporozoite rate for indoor resting mosquitoes was 8.6% and 4.2% for outdoors. In Kisian the sporozoite rate was 0.9% for indoor resting An. gambiae. None of the outdoor collected mosquitoes in Kisian tested positive for sporozoite infections. ConclusionThe study reports high densities of insecticide-resistant An. gambiae and An. funestus resting indoors and the persistence of malaria transmission indoors with high entomological inoculation rates (EIR) regardless of the use of Long-lasting insecticidal nets (LLINs). These findings underline the difficulties of controlling malaria vectors resting and biting indoors using the current interventions. Supplemental vector control tools and implementation of sustainable insecticide resistance management strategies are needed in western Kenya.

zoology↗

bioRxiv2019

uORFlight: a vehicle towards uORF-mediated translational regulation mechanisms in eukaryotes

Upstream open reading frames (uORFs) are prevalent in eukaryotic mRNAs. They act as a translational control element for precisely tuning the expression of the downstream major open reading frame (mORF) with essential cellular functionalities. uORF variation has been clearly associated with several human diseases. In contrast, natural uORF variants in plants have not ever been identified or linked with any phenotypic changes. The paucity of such evidence encouraged us to generate this database-uORFlight (http://uorflight.whu.edu.cn). It facilitates the exploration of uORF variation among different splicing models of Arabidopsis and rice genes. Most importantly, users can evaluate uORF frequency among different accessions at the population scale and find out the causal single nucleotide polymorphism (SNP) or insertion/deletion (INDEL) which can be associated with phenotypic variation through database mining or simple experiments. Such information will help to make hypotheses of uORF function in plant development or adaption to changing environments on the basis of the cognate mORF function. This database also curates plant uORF relevant literature into distinct groups. To be broadly interesting, our database expands uORF annotation into more species of fungi (Botrytis cinerea), plant (Brassica napus, Glycine max, Gossypium raimondii, Medicago truncatula, Solanum lycopersicum, Solanum tuberosum, Triticum aestivum and Zea mays), metazoan (Caenorhabditis elegans and Drosophila melanogaster) and vertebrate (Homo sapiens, Mus musculus and Danio rerio). Therefore, uORFlight will light up the runway toward how uORF genetic variation determines phenotypic diversity and advance our understanding of translational control mechanisms.

genomics↗

bioRxiv2019

Molecular basis for allosteric regulation of the type 2 ryanodine receptor channel gating by key modulators

The type-2 ryanodine receptor (RyR2) is responsible for releasing Ca2+ from the sarcoplasmic reticulum of cardiomyocytes, subsequently leading to muscle contraction. Here, we report four cryo-EM structures of porcine RyR2 bound to distinct modulators that collectively provide mechanistic insight into RyR2 regulation. Ca2+ alone induces a contraction of the Central domain that facilitates the dilation of S6 bundle, but is insufficient to open the pore. The small molecule agonist PCB95 helps Ca2+ to overcome the barrier for opening. FKBP12.6 induces a relaxation of the Central domain that decouples it from the S6 bundle, stabilizing RyR2 in a closed state. Caffeine locks the Central domain in a constitutively contracted state, while further addition of ATP opens the channel by strengthening the coupling between the U-motif and S6. Our study marks an important step towards mechanistic understanding of the complicated regulation of this key channel whose aberrant activity engenders life-threatening cardiac disorders.

biochemistry↗

bioRxiv2019

Metagenomic Next-generation Sequencing of Cerebrospinal Fluid for the Diagnosis of Central Nervous System Infections: A Multicentre Prospective Study

BackgroundInfectious encephalitis and meningitis are often treated empirically without identification of the causative pathogen. Metagenomic next-generation sequencing (mNGS) is a high throughput technology that enables the detection of pathogens independent of prior clinical or laboratory information.\n\nMethodsThe present study was a multicentre prospective evaluation of mNGS of cerebrospinal fluid (CSF) for the diagnosis of suspected central nervous system infections.\n\nResultsA total of 276 patients were enrolled in this study between Jan 1, 2017 and Jan 1, 2018. Identification of an etiologic pathogen in CSF by mNGS was achieved in 101 patients (36.6%). mNGS detected 11 bacterial species, 7 viral species, 2 fungal species, and 2 parasitic species. The five leading positive detections were varicella-zoster virus (17), Mycobacterium tuberculosis (14), herpes simplex virus 1 (12), Epstein-Barr virus (12), and Cryptococcus neoformans (7). False positives occurred in 12 (4.3%) patients with bacterial infections known to be widespread in hospital environments. False negatives occurred in 16 (5.8%) patients and included bacterial, viral and fungal aetiologies.\n\nConclusionsmNGS of CSF is a powerful diagnostic method to identify the pathogen for many central nervous system infections.

genomics↗

bioRxiv2019

Composition variation of agarwood-associated microbial communities from Aquilaria sinensis

Agarwood, derived from Aquilaria sinensis and Aquilaria malaccensis, is of medicinal and ecological value and religious importance as incense. The existing imbalance between short supply and increasing demand of this product remains to be solved. Thus, the biologically artificial agarwood-inducing methods commonly called whole-tree agarwood-inducing techniques (agar-wit) have been established to dramatically improve agarwood yield within a short period. However, several studies reported a lower content of ethanol-soluble extractive in the agar-wit agarwood than in the natural agarwood. To further understand the role of microorganisms in agarwood formation, we investigated and contrasted the endophytic bacteria and fungi between different types of agarwood from A. sinensis through high-throughput sequencing. Results showed that the same dominant phyla of bacteria consisting of Proteobacteria, Actinobacteria, and Acidobacteria were shared by the natural agarwood and agar-wit agarwood. Meanwhile, Ascomycota and Basidiomycota constituted the similar dominant fungal phyla of these two kinds of agarwood. However, the principal microbial communities at the genus or order level evidently varied from natural agarwood to agar-wit agarwood. Moreover, the bacterial communities are closely connected with terpenoid and carbohydrate metabolism, which indicated that the bacterial communities also play a vital role in agarwood formation. In conclusion, the higher concentrated abundance of the dominant microbial communities in agar-wit agarwood than in natural agarwood may promote agarwood formation, however, the low evenness of microbial communities also lowers the content of ethanol-soluble extractive.\n\nIMPORTANCEAgarwood has become an indispensable product in modern life because of medicinal value, ecological and religious importance as incense. Nevertheless, the enormous demand for agarwood markedly exceeds the supply because of the dramatically declining population of genus Aquilaria. Agarwood formation occurring slowly and infrequently in a natural environment, so various artificial techniques were developed to promote the formation of agarwood, such as the physical methods and chemical methods. However, these techniques still are insufficient to compensate for the agarwood shortage. In this case, a novel biological method called the whole-tree agarwood-inducing technique (Agar-wit) induces agarwood production. However, several studies have shown that agarwood harvested from biological technology contains lower content of ethanol-soluble extractive compared with natural agarwood. So to further expose and understand the endophytic bacteria and fungi in agarwood formation is important for the improvement of biological method.

plant biology↗

bioRxiv2019

Midgut Transcriptome Analysis of Clostera anachoreta Treated with Cry1Ac Toxin

Clostera anachoreta is one of the important Lepidoptera insect pests in forestry, especially in poplars woods in China, Europe, Japan and India, et al, and also the target insect of Cry1Ac toxin and Bt plants. In this study, by using the different dosages of Btcry1Ac toxin to feed larvae and analyzing the transcriptome data, we found six genes, HSC70, GNB2L/RACK1, PNLIP, BI1-like, arylphorin type 2 and PKM, might be associated with Cry1Ac toxin. And PI3K-Akt pathway, which was highly enriched in DEGs and linked to several crucial pathways, including the B cell receptor signaling pathway, toll-like receptor pathway, and MAPK signaling pathway, might be involved in the recovery stage when response to sub-lethal Cry1Ac toxin. This is the first study conducted to specifically investigate C. anachoreta response to Cry toxin stress using large-scale sequencing technologies, and the results highlighted some important genes and pathway that could be involved in Btcry1Ac resistance development or could serve as targets for biologically-based control mechanisms of this insect pest.

zoology↗

bioRxiv2019

Leveraging tissue specific gene expression regulation to identify genes associated with complex diseases

To increase statistical power to identify genes associated with complex traits, a number of transcriptome-wide association study (TWAS) methods have been proposed using gene expression as a mediating trait linking genetic variations and diseases. These methods first predict expression levels based on inferred expression quantitative trait loci (eQTLs) and then identify expression-mediated genetic effects on diseases by associating phenotypes with predicted expression levels. The success of these methods critically depends on the identification of eQTLs, which may not be functional in the corresponding tissue, due to linkage disequilibrium (LD) and the correlation of gene expression between tissues. Here, we introduce a new method called T-GEN (Transcriptome-mediated identification of disease-associated Gens with Epigenetic aNnotation) to identify disease-associated genes leveraging epigenetic information. Through prioritizing SNPs with tissue-specific epigenetic annotation, T-GEN can better identify SNPs that are both statistically predictive and biologically functional. We found that a significantly higher percentage (an increase of 18.7% to 47.2%) of eQTLs identified by T-GEN are inferred to be functional by ChromHMM and more are deleterious based on their Combined Annotation Dependent Depletion (CADD) scores. Applying T-GEN to 207 complex traits, we were able to identify more trait-associated genes (ranging from 7.7 % to 102%) than those from existing methods. Among the identified genes associated with these traits, T-GEN can better identify genes with high (>0.99) pLI scores compared to other methods. When T-GEN was applied to late-onset Alzheimers disease, we identified 96 genes located at 15 loci, including two novel loci not implicated in previous GWAS. We further replicated 50 genes in an independent GWAS, including one of the two novel loci. Author summaryTWAS-like methods have been widely applied to understand disease etiology using eQTL data and GWAS results. However, it is still challenging to discriminate the true disease-associated genes from those in strong LD with true genes, which is largely due to the misidentification of eQTLs. Here we introduce a novel statistical method named T-GEN to identify disease-associated genes considering epigenetic information. Compared to current TWAS methods, T-GEN can not only identify eQTLs with higher CADD scores and function potentials in gene-expression imputation models, but also identify more disease-associated genes across 207 traits and more genes with high (>0.99) pLI scores. Applying T-GEN in late-onset Alzheimers disease identified 96 genes at 15 loci with two novel loci. Among 96 identified genes, 50 genes were further replicated in an independent GWAS.

genetics↗

bioRxiv2018

Estimating prevalence for limb-girdle muscular dystrophy based on public sequencing databases

PurposeLimb Girdle Muscular Dystrophies (LGMD) are a genetically heterogeneous category of autosomal inherited muscle diseases. Many genes causing LGMD have been identified, and clinical trials are beginning for treatment of some genetic subtypes. However, even with the gene-level mechanisms known, it is still difficult to get a reliable and generalizable prevalence estimation for each subtype due to the limited amount of epidemiology data and the low incidence of LGMDs. MethodsTaking advantage of recently published whole exome and genome sequencing data from the general population, we used a Bayesian method to develop a reliable disease prevalence estimator. ResultsThis method was applied to nine recessive LGMD subtypes. The estimated disease prevalence calculated by this method were largely comparable to published estimates from epidemiological studies, however highlighted instances of possible under-diagnosis for LGMD2B and 2L. ConclusionThe increasing size of aggregated population variant databases will allow for robust and reproducible prevalence estimates of recessive disease, which is critical for the strategic design and prioritization of clinical trials.

epidemiology↗

bioRxiv2018

Lasagna: Multifaceted Protein-Protein Interaction Prediction Based on Siamese Residual RCNN

Sequence-based protein-protein interaction (PPI) prediction represents a fundamental computational biology problem. To address this problem, extensive research efforts have been made to extract predefined features from the sequences. Based on these features, statistical algorithms are learned to classify the PPIs. However, such explicit features are usually costly to extract, and typically have limited coverage on the PPI information. Hence, we present an end-to-end framework, Lasagna, for PPI predictions using only the primary sequences of a protein pair. Lasagna incorporates a deep residual recurrent convolutional neural network in the Siamese learning architecture, which leverages both robust local features and contextualized information that are significant for capturing the mutual influence of protein sequences. Our framework relieves the data pre-processing efforts that are required by other systems, and generalizes well to different application scenarios. Experimental evaluations show that Lasagna outperforms various state-of-the-art systems on the binary PPI prediction problem. Moreover, it shows a promising performance on more challenging problems of interaction type prediction and binding affinity estimation, where existing approaches fall short. The implementation of our framework is available at https://github.com/muhaochen/seq_ppi.git

bioinformatics↗

bioRxiv2018

The saturation gap: a simple transformation of oxygen saturation using virtual shunt

ObjectivePeripheral oxygen saturation (SpO2) obtained from pulse oximetry is a widely used physiological measurement. Clinical interpretation is limited by the nonlinear relationship between SpO2, degree of impairment in gas exchange, and effect of altitude. SpO2 is frequently dichotomized to overcome these limitations during prediction modelling. Using the known physiological relationship between virtual shunt and SpO2, we propose the saturation gap as a transformation of SpO2.\n\nApproachWe computed the theoretical virtual shunt corresponding to various SpO2 values and derived an accurate approximation formula between virtual shunt and SpO2. The approximation was based on previously described empiric observations and known physiological relationships. We evaluated the utility of the saturation gap in a clinical study predicting the need for facility admission in children in a rural health-care setting.\n\nMain ResultsThe transformation was saturation gap = 49.314*log10(103.711 - SpO2) -37.315. The ability to predict hospital admission based on a continuous variable SpO2 or saturation gap produced an identical area under the curve of 0.71 (95% CI: 0.69-0.73), compared to only 0.57 (CI: 0.56-0.58) based on diagnosis of hypoxemia (defined as SpO2<90%). However, SpO2 demonstrated a lack of fit compared to saturation gap (goodness-of-fit test p-value <0.0001 versus 0.098). The observed admission rates varied linearly with saturation gap but varied nonlinearly with SpO2.\n\nSignificanceThe saturation gap estimates a continuous linearly interpretable disease severity from SpO2 and improves clinical prediction models. The saturation gap will also allow for straightforward incorporation of altitude in interpretation of measurements of SpO2.

bioengineering↗

bioRxiv2018

Metabolically activated macrophages in mammary adipose tissue link obesity to triple-negative breast cancer

Obesity is associated with increased incidence and severity of triple-negative breast cancer (TNBC); however, mechanisms underlying this relationship are incompletely understood. Macrophages, which accumulate in adipose tissue and are activated during obesity, are an attractive mechanistic link. Here, we show that, during obesity, murine and human mammary adipose tissue macrophages adopt a pro-inflammatory, metabolically- activated (MMe) macrophage phenotype that promotes TNBC stem-like markers and functions, including increased tumorsphere growth in vitro and tumor-initiating potential in vivo. We demonstrate that MMe macrophages release cytokines in an NADPH oxidase 2 (NOX2)-dependent manner that signal through glycoprotein 130 (GP130) on TNBC cells to promote their stem-like properties. Accordingly, deleting Nox2 in myeloid cells or depleting GP130 in TNBC cells attenuates the ability of obesity to drive TNBC tumor formation. Our studies implicate MMe macrophage accumulation in mammary adipose tissue during obesity as a mechanism for promoting TNBC stemness and tumorigenesis.\n\nHIGHLIGHTS Obesity promotes TNBC tumor formation and stemness.\nMammary adipose tissue macrophages are metabolically activated (MMe) in obese mice and humans.\nMMe macrophages in mammary adipose tissue contribute to obesity-induced stemness.\nMMe macrophages promote TNBC stemness through GP130 signaling.

cancer biology↗

bioRxiv2018

Rice Galaxy: an open resource for plant science

Background\n\nRice molecular genetics, breeding, genetic diversity, and allied research (such as rice-pathogen interaction) have adopted sequencing technologies and high density genotyping platforms for genome variation analysis and gene discovery. Germplasm collections representing rice diversity, improved varieties and elite breeding materials are accessible through rice gene banks for use in research and breeding, with many having genome sequences and high density genotype data available. Combining phenotypic and genotypic information on these accessions enables genome-wide association analysis, which is driving quantitative trait loci (QTL) discovery and molecular marker development. Comparative sequence analyses across QTL regions facilitate the discovery of novel alleles. Analyses involving DNA sequences and large genotyping matrices for thousands of samples, however, pose a challenge to non-computer savvy rice researchers.\n\nFindings\n\nWe adopted the Galaxy framework to build the federated Rice Galaxy resource, with shared datasets, tools, and analysis workflows relevant to rice research. The shared datasets include high density genotypes from the 3,000 Rice Genomes project and sequences with corresponding annotations from nine published rice genomes. Rice Galaxy includes tools for designing single nucleotide polymorphism (SNP) assays, analyzing genome-wide association studies, population diversity, rice-bacterial pathogen diagnostics, and a suite of published genomic prediction methods. A prototype Rice Galaxy compliant to Open Access, Open Data, and Findable, Accessible, Interoperable, and Reproducible principles is also presented.\n\nConclusions\n\nRice Galaxy is a freely available resource that empowers the plant research community to perform state-of-the-art analyses and utilize publicly available big datasets for both fundamental and applied science.

bioinformatics↗

bioRxiv2018

Base pair editing of goat embryos: nonsense codon introgression into FGF5 to improve cashmere yield

The ability to alter single bases without DNA double strand breaks provides a potential solution for multiplex editing of livestock genomes for quantitative traits. Here, we report using a single base editing system, Base Editor 3 (BE3), to induce nonsense codons (C-to-T transitions) at four target sites in caprine FGF5. All five progenies produced from microinjected single-cell embryos had alleles with a targeted nonsense mutation and yielded expected phenotypes. The effectiveness of BE3 to make single base changes varied considerably based on sgRNA design. Also, the rate of mosaicism differed between animals, target sites, and tissue type. PCR amplicon and whole genome resequencing analyses for off-target changes caused by BE3 were low at a genome-wide scale. This study provides first evidence of base editing in livestock, thus presenting a potentially better method to introgress complex human disease alleles into large animal models and provide genetic improvement of complex health and production traits in a single generation.

genetics↗

bioRxiv2018

Base-pair Ambiguity and the Kinetics of RNA Folding: a Hypothesis-Driven Statistical Analysis

BackgroundA folding RNA molecule encounters multiple opportunities to form non-native yet energetically favorable pairings of nucleotide sequences. Given this forbidding free-energy landscape, mechanisms have evolved that contribute to a directed and efficient folding process, including catalytic proteins and error-detecting chaperones. Among structural RNA molecules we make a distinction between \"bound\" molecules, which are active as part of ribonucleoprotein (RNP) complexes, and \"unbound,\" with physiological functions performed without necessarily being bound in RNP complexes. We hypothesized that unbound molecules, lacking the partnering structure of a protein, would be more vulnerable than bound molecules to kinetic traps that compete with native stem structures. We defined an \"ambiguity index\"--a normalized function of the primary and secondary structure of an individual molecule that measures the number of kinetic traps available to nucleotide sequences that are paired in the native structure, presuming that unbound molecules would have lower indexes. The ambiguity index depends on the purported secondary structure, and was computed under both the comparative (\"gold standard\") and an equilibrium-based prediction which approximates the minimum free energy (MFE) structure. Arguing that kinetically accessible metastable structures might be more biologically relevant than thermodynamic equilibrium structures, we also hypothesized that MFE-derived ambiguities would be less effective in separating bound and unbound molecules.\n\nResultsWe have introduced an intuitive and easily computed function of primary and secondary structures that measures the availability of complementary sequences that could disrupt the formation of native stems on a given molecule--an ambiguity index. Using comparative secondary structures, the ambiguity index is systematically smaller among unbound than bound molecules, as expected. Furthermore, the effect is lost when the presumably more accurate comparative structure is replaced instead by the MFE structure.\n\nConclusionsA statistical analysis of the relationship between the primary and secondary structures of non-coding RNA molecules suggests that stem-disrupting kinetic traps are substantially less prevalent in molecules not participating in RNP complexes. In that this distinction is apparent under the comparative but not the MFE secondary structure, the results highlight a possible deficiency in structure predictions when based upon assumptions of thermodynamic equilibrium.

bioinformatics↗

bioRxiv2018

Temporal changes in gut microbiota and signaling molecules of the gut-brain axis in mice fed meat protein diets

The purpose of this study was to characterize the dynamical changes of gut microbiota and explore the influence on bidirectional communications between the gut and the brain during a relatively long-term intake of different protein diets. The C57BL/6J mice were fed casein, soy protein and four kinds of processed meat proteins at a normal dose of 20% for 8 months. Protein diets dramatically affected the microbial composition and function and also the signaling molecule levels of the gut-brain axis in a dynamic manner, which consequently affected growth performance. Alistipes, Clostridiales vadinBB60, Anaerotruncus, Blautia and Oscillibacter had a relatively fast response to the diet, while Bacteroidales S24-7, Ruminiclostridium, Ruminococcaceae UCG-014, Coriobacteriaceae UCG-002 and Bilophila responded slowly. Rikenellaceae RC9 gut, Faecalibaculum and Lachnospiraceae showed a continuous change with feeding time. Bacteroidales S24-7 abundance increased from 4 months to 8 months, whereas those of Rikenellaceae RC9 gut, Akkermansia, Alistipes and Anaerotruncus remarkably decreased. Five and fifteen biological functions of microbiota were affected at 4 months and 8 months, respectively, and sixteen functions were observed to change over feeding time. Moreover, 28 and 48 specific operational taxonomy units were associated with the regulation of serotonin, peptide YY, leptin and insulin levels at two time points. Ruminococcaceae was positively associated with Lachnospiraceae and negatively associated with Bacteroidales S24-7. These results give an important insight into the effect of gut microbiota on the bidirectional communications between the gut and the brain under a certain type of diet.\n\nImportanceMany gastrointestinal and neuropsychiatric disorders may have a common pathophysiologic mechanism, involving bidirectional brain-gut axis signaling through humoral and neural pathways. The gut microbiota plays an important role in the communications between the gut and the brain. Recent evidence suggests that a growing number of subjects suffer from the above disorders. The significance of this study lies in the finding that long-term intake of different proteins at a normal dose induces dynamic alterations of specific microbiota in mice, which consequently affect bidirectional communications between the gut and the brain and results in different growth performance through dynamically regulating signaling molecule levels. Furthermore, this study indicates that intake of the same diet for a long time, irrespective of the diet source, may have an adverse effect on host health by altering gut microbiota.

microbiology↗