scholarly journals Gut-derived Metabolites Influence Neurodevelopmental Gene Expression and Wnt Signalling Events in a Germ-free Zebrafish Model

Author(s):  
Terry Van Raay ◽  
Victoria Rea ◽  
Ian Bell

Abstract Background : Small molecule metabolites produced by the microbiome are known to be neuroactive and are capable of directly impacting the brain and central nervous system, yet there is little data on the contribution of these metabolites to the earliest stages of neural development and neural gene expression. Here, we explore the impact of deriving zebrafish embryos in the absence of microbes on early neural development as well as investigate whether any potential changes can be rescued with treatment of metabolites derived from the zebrafish gut microbiota. Results : Overall, we did not observe any gross morphological changes between treatments but did observe a significant decrease in neural gene expression in embryos raised germ-free, which was rescued with the addition of zebrafish metabolites. Specifically, we identified 354 genes significantly down regulated in germ-free embryos compared to conventionally raised embryos via RNA-Seq analysis. Of these, 42 were rescued with a single treatment of zebrafish gut-derived metabolites to germ-free embryos. Gene ontology analysis revealed that these genes are involved in prominent neurodevelopmental pathways including transcriptional regulation and Wnt signalling. Consistent with the ontology analysis, we found alterations in the development of Wnt dependent events which was rescued in the germ-free embryos treated with metabolites. Conclusions : These findings demonstrate that gut-derived metabolites are in part responsible for regulating critical signalling pathways in the brain, especially during neural development.

2021 ◽  
Author(s):  
Victoria Rea ◽  
Ian Bell ◽  
Terence J Van Raay

Small molecule metabolites produced by the microbiome are known to be neuroactive and are capable of directly impacting the brain and central nervous system, yet there is little data on the contribution of these metabolites to the earliest stages of neural development and neural gene expression. Here, we explore the impact of rearing zebrafish embryos in the absence of microbes on early neural development as well as investigate whether any potential changes can be rescued with treatment of metabolites derived from the zebrafish gut microbiota. Overall, we did not observe any gross morphological changes between treatments but did observe a significant decrease in neural gene expression in embryos raised germ-free, which was rescued with the addition of zebrafish metabolites. Specifically, we identified 361 genes significantly down regulated in GF embryos compared to conventionally raised embryos via RNA-Seq analysis. Of these, 42 were rescued with the treatment of zebrafish gut-derived metabolites to GF embryos. Gene ontology analysis revealed that these genes are involved in prominent neurodevelopmental pathways including transcriptional regulation and Wnt signalling. Consistent with the ontology analysis, we found alterations in the development of Wnt dependent events which is rescued in the GF embryos treated with metabolites.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Li Tong ◽  
◽  
Po-Yen Wu ◽  
John H. Phan ◽  
Hamid R. Hassazadeh ◽  
...  

Abstract To use next-generation sequencing technology such as RNA-seq for medical and health applications, choosing proper analysis methods for biomarker identification remains a critical challenge for most users. The US Food and Drug Administration (FDA) has led the Sequencing Quality Control (SEQC) project to conduct a comprehensive investigation of 278 representative RNA-seq data analysis pipelines consisting of 13 sequence mapping, three quantification, and seven normalization methods. In this article, we focused on the impact of the joint effects of RNA-seq pipelines on gene expression estimation as well as the downstream prediction of disease outcomes. First, we developed and applied three metrics (i.e., accuracy, precision, and reliability) to quantitatively evaluate each pipeline’s performance on gene expression estimation. We then investigated the correlation between the proposed metrics and the downstream prediction performance using two real-world cancer datasets (i.e., SEQC neuroblastoma dataset and the NIH/NCI TCGA lung adenocarcinoma dataset). We found that RNA-seq pipeline components jointly and significantly impacted the accuracy of gene expression estimation, and its impact was extended to the downstream prediction of these cancer outcomes. Specifically, RNA-seq pipelines that produced more accurate, precise, and reliable gene expression estimation tended to perform better in the prediction of disease outcome. In the end, we provided scenarios as guidelines for users to use these three metrics to select sensible RNA-seq pipelines for the improved accuracy, precision, and reliability of gene expression estimation, which lead to the improved downstream gene expression-based prediction of disease outcome.


2020 ◽  
Author(s):  
Colin Peter Singer Kruse ◽  
Alexander D Meyers ◽  
Proma Basu ◽  
Sarahann Hutchinson ◽  
Darron R Luesse ◽  
...  

Abstract Background: Understanding of gravity sensing and response is critical to long-term human habitation in space and can provide new advantages for terrestrial agriculture. To this end, the altered gene expression profile induced by microgravity has been repeatedly queried by microarray and RNA-seq experiments to understand gravitropism. However, the quantification of altered protein abundance in space has been minimally investigated. Results: Proteomic (iTRAQ-labelled LC-MS/MS) and transcriptomic (RNA-seq) analyses simultaneously quantified protein and transcript differential expression of three-day old, etiolated Arabidopsis thaliana seedlings grown aboard the International Space Station along with their ground control counterparts. Protein extracts were fractionated to isolate soluble and membrane proteins and analyzed to detect differentially phosphorylated peptides. In total, 968 RNAs, 107 soluble proteins, and 103 membrane proteins were identified as differentially expressed. In addition, the proteomic analyses identified 16 differential phosphorylation events. Proteomic data delivered novel insights and simultaneously provided new context to previously made observations of gene expression in microgravity. There is a sweeping shift in post-transcriptional mechanisms of gene regulation including RNA-decapping protein DCP5, the splicing factors GRP7 and GRP8, and AGO4,. These data also indicate AHA2 and FERONIA as well as CESA1 and SHOU4 as central to the cell wall adaptations seen in spaceflight. Patterns of tubulin-a 1, 3,4 and 6 phosphorylation further reveal an interaction of microtubule and redox homeostasis that mirrors osmotic response signaling elements. The absence of gravity also results in a seemingly wasteful dysregulation of plastid gene transcription. Conclusions: The datasets gathered from Arabidopsis seedlings exposed to microgravity revealed marked impacts on post-transcriptional regulation, cell wall synthesis, redox/microtubule dynamics, and plastid gene transcription. The impact of post-transcriptional regulatory alterations represents an unstudied element of the plant microgravity response with the potential to significantly impact plant growth efficiency and beyond. What’s more, addressing the effects of microgravity on AHA2, CESA1, and alpha tubulins has the potential to enhance cytoskeletal organization and cell wall composition, thereby enhancing biomass production and growth in microgravity. Finally, understanding and manipulating the dysregulation of plastid gene transcription has further potential to address the goal of enhancing plant growth in the stressful conditions of microgravity.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Bastiaan H. A. Urbanus ◽  
Saša Peter ◽  
Simon E. Fisher ◽  
Chris I. De Zeeuw

AbstractFOXP2 has been identified as a gene related to speech in humans, based on rare mutations that yield significant impairments in speech at the level of both motor performance and language comprehension. Disruptions of the murine orthologue Foxp2 in mouse pups have been shown to interfere with production of ultrasonic vocalizations (USVs). However, it remains unclear which structures are responsible for these deficits. Here, we show that conditional knockout mice with selective Foxp2 deletions targeting the cerebral cortex, striatum or cerebellum, three key sites of motor control with robust neural gene expression, do not recapture the profile of pup USV deficits observed in mice with global disruptions of this gene. Moreover, we observed that global Foxp2 knockout pups show substantive reductions in USV production as well as an overproduction of short broadband noise “clicks”, which was not present in the brain region-specific knockouts. These data indicate that deficits of Foxp2 expression in the cortex, striatum or cerebellum cannot solely explain the disrupted vocalization behaviours in global Foxp2 knockouts. Our findings raise the possibility that the impact of Foxp2 disruption on USV is mediated at least in part by effects of this gene on the anatomical prerequisites for vocalizing.


2006 ◽  
Vol 54 (1) ◽  
pp. 247-255 ◽  
Author(s):  
J.R. Liu ◽  
C.T. Liu ◽  
E.A. Edwards ◽  
S.N. Liss

The effect of limiting phosphorus (P) in activated sludge was investigated in laboratory-scale sequencing batch reactors (SBRs). Correlative microscopy revealed that P-limitation (COD:N:P=100:5:0.05) leads to morphological changes in floc structure and the composition of extracellular polymeric substances (EPS). This was found to be accompanied by expression of quorum-sensing in an acyl homoserine lactone bioassay. Differential gene expression in relation to P-limitation was examined in a global profile using the Affymetrix™ Escherichia coli antisense genomic microarray. Three separate experiments were conducted where the impact of P-limitation was examined under batch conditions and in SBRs at stable operating conditions and within 3–7 days following a down-shift in P. Significant changes in open reading frames (ORF) and intergenic regions based on the E. coli microarray were observed. Several genes associated with cell structure, including slt, wbbH, fimH, amB, rfaJ and slp were found to be expressed. Quorum regulated genes were also found to be expressed including psiF which is known to be induced by P-starvation (92% confidence level; 1.45 log ratio).


2020 ◽  
Author(s):  
Hiroto Yamamoto ◽  
Yutaro Uchida ◽  
Tomoki Chiba ◽  
Ryota Kurimoto ◽  
Takahide Matsushima ◽  
...  

AbstractBackgroundsSevoflurane is a most frequently used volatile anaesthetics, but its molecular mechanisms of action remain unclear. We hypothesized that specific genes play regulatory roles in whole brain exposed to sevoflurane. Thus, we aimed to evaluate the effects of sevoflurane inhalation and identify potential regulatory genes by RNA-seq analysis.MethodsEight-week old mice were exposed to sevoflurane. RNA from four medial prefrontal cortex, striatum, hypothalamus, and hippocampus were analysed using RNA-seq. Differently expressed genes were extracted. Their gene ontology terms and the transcriptome array data of the cerebral cortex of sleeping mice were analysed using Metascape, and the gene expression patterns were compared. Finally, the activities of transcription factors were evaluated using a weighted parametric gene set analysis (wPGSA). JASPAR was used to confirm the existence of binding motifs in the upstream sequences of the differently expressed genes.ResultsThe gene ontology term enrichment analysis result suggests that sevoflurane inhalation upregulated angiogenesis and downregulated neural differentiation in the whole brain. The comparison with the brains of sleeping mice showed that the gene expression changes were specific to anaesthetized mice. Sevoflurane induced Klf4 upregulation in the whole brain. The transcriptional analysis result suggests that KLF4 is a potential transcriptional regulator of angiogenesis and neural development.ConclusionsKlf4 was upregulated by sevoflurane inhalation in whole brain. KLF4 might promote angiogenesis and cause the appearance of undifferentiated neural cells by transcriptional regulation. The roles of KLF4 might be key to elucidating the mechanisms of sevoflurane induced functional modification in the brain.


2020 ◽  
Author(s):  
Paulina G. Eusebi ◽  
Natalia Sevane ◽  
Thomas O’Rourke ◽  
Manuel Pizarro ◽  
Cedric Boeckx ◽  
...  

AbstractAggressiveness is one of the most basic behaviors, characterized by targeted intentional actions oriented to cause harm. The reactive type of aggression is regulated mostly by the brain’s prefrontal cortex; however, the molecular changes underlying aggressiveness in adults have not been fully characterized. Here we used an RNA-seq approach to investigate differential gene expression in the prefrontal cortex of bovines from the aggressive Lidia breed at different age stages: young three-year old and adult four-year-old bulls. A total of 50 up and 193 down-regulated genes in the adult group were identified. Furthermore, a cross-species comparative analysis retrieved 29 genes in common with previous studies on aggressive behaviors, representing an above-chance overlap with the differentially expressed genes in adult bulls.Particularly, we detected changes in the regulation of networks such as synaptogenesis, involved in maintenance and refinement of synapses, and the glutamate receptor pathway, which acts as excitatory driver in aggressive responses. Our results provide insights into candidate genes and networks involved in the molecular mechanisms leading to the maturation of the brain. The reduced reactive aggression typical of domestication has been proposed to form part of a retention of juvenile traits as adults (neoteny). The significant age-associated differential expression of genes implicated in aggressive behaviors and concomitant increase in Lidia cattle aggression validates this species as a novel model comparator to explore the impact of behavioral neoteny under domestication.


2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Yingmei Li ◽  
Dina Polyak ◽  
Layton Lamsam ◽  
Ian David Connolly ◽  
Eli Johnson ◽  
...  

AbstractNon-small cell lung cancer (NSCLC) metastatic to the brain leptomeninges is rapidly fatal, cannot be biopsied, and cancer cells in the cerebrospinal fluid (CSF) are few; therefore, available tissue samples to develop effective treatments are severely limited. This study aimed to converge single-cell RNA-seq and cell-free RNA (cfRNA) analyses to both diagnose NSCLC leptomeningeal metastases (LM), and to use gene expression profiles to understand progression mechanisms of NSCLC in the brain leptomeninges. NSCLC patients with suspected LM underwent withdrawal of CSF via lumbar puncture. Four cytology-positive CSF samples underwent single-cell capture (n = 197 cells) by microfluidic chip. Using robust principal component analyses, NSCLC LM cell gene expression was compared to immune cells. Massively parallel qPCR (9216 simultaneous reactions) on human CSF cfRNA samples compared the relative gene expression of patients with NSCLC LM (n = 14) to non-tumor controls (n = 7). The NSCLC-associated gene, CEACAM6, underwent in vitro validation in NSCLC cell lines for involvement in pathologic behaviors characteristic of LM. NSCLC LM gene expression revealed by single-cell RNA-seq was also reflected in CSF cfRNA of cytology-positive patients. Tumor-associated cfRNA (e.g., CEACAM6, MUC1) was present in NSCLC LM patients’ CSF, but not in controls (CEACAM6 detection sensitivity 88.24% and specificity 100%). Cell migration in NSCLC cell lines was directly proportional to CEACAM6 expression, suggesting a role in disease progression. NSCLC-associated cfRNA is detectable in the CSF of patients with LM, and corresponds to the gene expression profile of NSCLC LM cells. CEACAM6 contributes significantly to NSCLC migration, a hallmark of LM pathophysiology.


2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Kayla A. Johnson ◽  
Arjun Krishnan

Abstract Background Constructing gene coexpression networks is a powerful approach for analyzing high-throughput gene expression data towards module identification, gene function prediction, and disease-gene prioritization. While optimal workflows for constructing coexpression networks, including good choices for data pre-processing, normalization, and network transformation, have been developed for microarray-based expression data, such well-tested choices do not exist for RNA-seq data. Almost all studies that compare data processing and normalization methods for RNA-seq focus on the end goal of determining differential gene expression. Results Here, we present a comprehensive benchmarking and analysis of 36 different workflows, each with a unique set of normalization and network transformation methods, for constructing coexpression networks from RNA-seq datasets. We test these workflows on both large, homogenous datasets and small, heterogeneous datasets from various labs. We analyze the workflows in terms of aggregate performance, individual method choices, and the impact of multiple dataset experimental factors. Our results demonstrate that between-sample normalization has the biggest impact, with counts adjusted by size factors producing networks that most accurately recapitulate known tissue-naive and tissue-aware gene functional relationships. Conclusions Based on this work, we provide concrete recommendations on robust procedures for building an accurate coexpression network from an RNA-seq dataset. In addition, researchers can examine all the results in great detail at https://krishnanlab.github.io/RNAseq_coexpression to make appropriate choices for coexpression analysis based on the experimental factors of their RNA-seq dataset.


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