In-organoid single-cell CRISPR screening reveals determinants of hepatocyte differentiation and maturation

BACKGROUND

Harnessing hepatocytes for basic research and regenerative medicine demands a complete understanding of the genetic determinants underlying hepatocyte differentiation and maturation. Single-cell CRISPR screens in organoids could link genetic perturbations with parallel transcriptomic readout in single cells, providing a powerful method to delineate roles of cell fate regulators. However, a big challenge for identifying key regulators during data analysis is the low expression levels of transcription factors (TFs), which are difficult to accurately estimate due to noise and dropouts in single-cell sequencing. Also, it is often the changes in TF activities in the transcriptional cascade rather than the expression levels of TFs that are relevant to the cell fate transition.

RESULTS

Here, we develop Organoid-based Single-cell CRISPR screening Analyzed with Regulons (OSCAR), a framework using regulon activities as readouts to dissect gene knockout effects in organoids. In adult-stem-cell-derived liver organoids, we map transcriptomes in 80,576 cells upon 246 perturbations associated with transcriptional regulation of hepatocyte formation. Using OSCAR, we identify known and novel positive and negative regulators, among which Fos and Ubr5 are the top-ranked ones. Further single-gene loss-of-function assays demonstrate that Fos depletion in mouse and human liver organoids promote hepatocyte differentiation by specific upregulation of liver metabolic genes and pathways, and conditional knockout of Ubr5 in mouse liver delays hepatocyte maturation.

CONCLUSIONS

Altogether, we provide a framework to explore lineage specifiers in a rapid and systematic manner, and identify hepatocyte determinators with potential clinical applications.

TBX3 regulates the transcription of VEGFA to promote osteoblasts proliferation and microvascular regeneration

Objective

Osteochondral decellularization can promote local vascular regeneration, but the exact mechanism is unknown. The aim of this study is to study osteogenic microvascular regeneration in single cells.

Methods

The scRNA-seq dataset of human periosteal-derived cells (hPDCs) were analyzed by pySCENIC. To examine the role of TBX3 in osteogenesis and vascularization, cell transfection, qRT-PCR, western blot, and CCK-8 cell proliferation assays were performed.

Results

TCF7L2, TBX3, FLI1, NFKB2, and EZH2 were found to be transcription factors (TFs) most closely associated with corresponding cells. The regulatory network of these TFs was then visualized. Our study knocked down the expression of TBX3 in human osteoblast cell lines. In the TBX3 knockdown group, we observed decreased expression of VEGFA, VEGFB, and VEGFC. Moreover, Western blot analysis showed that downregulating TBX3 resulted in a reduction of VEGFA expression. And TBX3 stimulated osteoblast proliferation in CCK-8 assays.

Conclusion

TBX3 regulates VEGFA expression and promotes osteoblast proliferation in skeletal microvasculature formation. The findings provide a theoretical basis for investigating the role of TBX3 in promoting local vascular regeneration.

Determination of the regulatory network and function of the lysR-type transcriptional regulator of Lactiplantibacillus plantarum, LpLttR

Background

Lactiplantibacillus plantarum has various healthcare functions including the regulation of immunity and inflammation, reduction of serum cholesterol levels, anti-tumor activity, and maintenance of the balance of intestinal flora. However, the underlying metabolic and regulatory mechanisms of these processes remain unclear. Our previous studies have shown that the LysR type transcriptional regulator of L. plantarum (LpLttR) regulates the biotransformation of conjugated linoleic acids (CLAs) through the transcriptional activation of cla-dh (coding gene for CLA short-chain dehydrogenase) and cla-dc (coding gene for CLA acetoacetate decarboxylase). However, the regulatory network and function of LpLttR have not yet been characterized in L. plantarum.

Results

In this study, the regulatory role of LpLttR in various cellular processes was assessed using transcriptome analysis. The deletion of LpLttR had no evident influence on the bacterial growth. The transcriptome data showed that the expression of nine genes were positively regulated by LpLttR, and the expression of only two genes were negatively regulated. Through binding motif analysis and molecular interaction, we demonstrated that the regulatory region of the directly regulated genes contained a highly conserved sequence, consisting of a 15-base long box and rich in AT.

Conclusion

This study revealed that LpLttR of L. plantarum did not play a global regulatory role similar to that of the other transcriptional regulators in this family. This study broadens our knowledge of LpLttR and provides a theoretical basis for the utilization of L. plantarum.

Methods to Analyze the Developmental Trajectory of Human Primary NK Cells Using Monocle and SCENIC Analyses

Development of novel cellular therapies based on primary human NK cells is under active investigation. Human NK cells are comprised of distinct subsets with high transcriptomic heterogeneity. Unique methodologies are being developed to determine the transcriptomic profiles of human NK cells. NK cells account for 10-20% of total lymphocytes in the human peripheral blood, which mediates anti-tumor and anti-viral effector functions. Therapeutic success in the clinic depends on a better understanding of the single-cell transcriptome of human NK cell subsets. Moreover, a better understanding of the transcriptional network that regulates NK cell development, subset specification, and terminal maturation is obligatory for their in vitro generation and expansion toward clinical utilization. Here, we describe the procedure for single-cell RNA-sequencing of human NK cells and strategies for bioinformatic analyses. This protocol provides a data analysis roadmap for investigators who work on the basic biology and therapeutic applications of human NK cells.

Flexible comparative genomics of prokaryotic transcriptional regulatory networks

Background

Comparative genomics methods enable the reconstruction of bacterial regulatory networks using available experimental data. In spite of their potential for accelerating research into the composition and evolution of bacterial regulons, few comparative genomics suites have been developed for the automated analysis of these regulatory systems. Available solutions typically rely on precomputed databases for operon and ortholog predictions, limiting the scope of analyses to processed complete genomes, and several key issues such as the transfer of experimental information or the integration of regulatory information in a probabilistic setting remain largely unaddressed.

Results

Here we introduce CGB, a flexible platform for comparative genomics of prokaryotic regulons. CGB has few external dependencies and enables fully customized analyses of newly available genome data. The platform automates the merging of experimental information and uses a gene-centered, Bayesian framework to generate and integrate easily interpretable results. We demonstrate its flexibility and power by analyzing the evolution of type III secretion system regulation in pathogenic Proteobacteria and by characterizing the SOS regulon of a new bacterial phylum, the Balneolaeota.

Conclusions

Our results demonstrate the applicability of the CGB pipeline in multiple settings. CGB’s ability to automatically integrate experimental information from multiple sources and use complete and draft genomic data, coupled with its non-reliance on precomputed databases and its easily interpretable display of gene-centered posterior probabilities of regulation provide users with an unprecedented level of flexibility in launching comparative genomics analyses of prokaryotic transcriptional regulatory networks. The analyses of type III secretion and SOS response regulatory networks illustrate instances of convergent and divergent evolution of these regulatory systems, showcasing the power of formal ancestral state reconstruction at inferring the evolutionary history of regulatory networks.

Phenotypes, transcriptome, and novel biofilm formation associated with the ydcI gene

The ydcI gene has previously been shown to encode a DNA-binding protein involved with acid stress resistance and induced biofilm formation in a strain of Salmonella enterica serovar Typhimurium. In addition, characterisation of the ydcI gene in Escherichia coli and other bacteria demonstrated strikingly different tolerance for induced ydcI expression across Gram negative species. In this report, we investigated the conservation of these phenotypes across multiple strains of S. Typhimurium and E. coli, and we used RNA Seq to identify the transcriptome of the ΔydcI mutant compared to WT in S. Typhimurium and E. coli (to establish the YdcI regulon in each species). We constructed deletion mutants in each species based on the RNA Seq results and tested these mutants for the relevant ydcI-related phenotypes. Though no evidence for a role in these phenotypes was found via the RNA Seq deletion mutants, we found that the ydcI-induced biofilm in S. Typhimurium is formed independently of the major biofilm genes csgA and bcsA indicating a potentially novel type of biofilm formation.

RNA-seq from archival FFPE breast cancer samples: molecular pathway fidelity and novel discovery

BACKGROUND

Formalin-fixed, paraffin-embedded (FFPE) tissues for RNA-seq have advantages over fresh frozen tissue including abundance and availability, connection to rich clinical data, and association with patient outcomes. However, FFPE-derived RNA is highly degraded and chemically modified, which impacts its utility as a faithful source for biological inquiry.

METHODS

True archival FFPE breast cancer cases (n = 58), stored at room temperature for 2-23 years, were utilized to identify key steps in tissue selection, RNA isolation, and library choice. Gene expression fidelity was evaluated by comparing FFPE data to public data obtained from fresh tissues, and by employing single-gene, gene set and transcription network-based regulon analyses.

RESULTS

We report a single 10 μm section of breast tissue yields sufficient RNA for RNA-seq, and a relationship between RNA quality and block age that was not linear. We find single-gene analysis is limiting with FFPE tissues, while targeted gene set approaches effectively distinguish ER+ from ER- breast cancers. Novel utilization of regulon analysis identified the transcription factor KDM4B to associate with ER+ disease, with KDM4B regulon activity and gene expression having prognostic significance in an independent cohort of ER+ cases.

CONCLUSION

Our results, which outline a robust FFPE-RNA-seq pipeline for broad use, support utilizing FFPE tissues to address key questions in the breast cancer field, including the delineation between indolent and life-threatening disease, biological stratification and molecular mechanisms of treatment resistance.

Methods to Study Solo/Orphan Quorum-Sensing Receptors

LuxR solos/orphans are very widespread among Proteobacteria; however they are surprisingly understudied given that they are likely to play a major role in cell-cell communication in bacteria. Here we describe three simple methodologies/approaches that can be used in order to begin to study this subgroup of quorum sensing-related LuxR receptors.

Production of amino acids - Genetic and metabolic engineering approaches

The biotechnological production of amino acids occurs at the million-ton scale and annually about 6milliontons of l-glutamate and l-lysine are produced by Escherichia coli and Corynebacterium glutamicum strains. l-glutamate and l-lysine production from starch hydrolysates and molasses is very efficient and access to alternative carbon sources and new products has been enabled by metabolic engineering. This review focusses on genetic and metabolic engineering of amino acid producing strains. In particular, rational approaches involving modulation of transcriptional regulators, regulons, and attenuators will be discussed. To address current limitations of metabolic engineering, this article gives insights on recent systems metabolic engineering approaches based on functional tools and method such as genome reduction, amino acid sensors based on transcriptional regulators and riboswitches, CRISPR interference, small regulatory RNAs, DNA scaffolding, and optogenetic control, and discusses future prospects.

Regulation of bacterial heat shock stimulons

All organisms developed genetic programs to allow their survival under stressful conditions. In most cases, they increase the amount of a specific class of proteins which deal with the stress factor and allow cells to adapt to life-threatening conditions. One class of stress proteins are the heat shock proteins (HSPs) the amount of which is significantly increased after a sudden temperature rise. How is the heat shock response (HSR) regulated in bacteria? This has been studied in detail in Escherichia coli, Bacillus subtilis and Streptomyces spp. Two major mechanisms have been described so far to regulate expression of the HSGs, namely alternative sigma factors and transcriptional repressors. This review focuses on the regulatory details of the different heat shock regulons in the three well-studied bacterial species.

Assessment of transfer methods for comparative genomics of regulatory networks in bacteria

Background

Comparative genomics can leverage the vast amount of available genomic sequences to reconstruct and analyze transcriptional regulatory networks in Bacteria, but the efficacy of this approach hinges on the ability to transfer regulatory network information from reference species to the genomes under analysis. Several methods have been proposed to transfer regulatory information between bacterial species, but the paucity and distributed nature of experimental information on bacterial transcriptional networks have prevented their systematic evaluation.

Results

We report the compilation of a large catalog of transcription factor-binding sites across Bacteria and its use to systematically benchmark proposed transfer methods across pairs of bacterial species. We evaluate motif- and accuracy-based metrics to assess the results of regulatory network transfer and we identify the precision-recall area-under-the-curve as the best metric for this purpose due to the large class-imbalanced nature of the problem. Methods assuming conservation of the transcription factor-binding motif (motif-based) are shown to substantially outperform those assuming conservation of regulon composition (network-based), even though their efficiency can decrease sharply with increasing phylogenetic distance. Variations of the basic motif-based transfer method do not yield significant improvements in transfer accuracy. Our results indicate that detection of a large enough number of regulated orthologs is critical for network-based transfer methods, but that relaxing orthology requirements does not improve results. Using the transcriptional regulators LexA and Fur as case examples, we also show how DNA-binding domain sequence similarity can yield confounding results as an indicator of transfer efficiency for motif-based methods.

Conclusions

Counter to standard practice, our evaluation of metrics to assess the efficiency of methods for regulatory network information transfer reveals that the area under precision-recall (PR) curves is a more precise and informative metric than that of receiver-operating-characteristic (ROC) curves, confirming similar findings in other class-imbalanced settings. Our systematic assessment of transfer methods reveals that simple approaches to both motif- and network-based transfer of regulatory information provide equal or better results than more elaborate methods. We also show that there are not effective predictors of transfer efficacy, substantiating the long-standing practice of manual curation in comparative genomics analyses.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1113-7) contains supplementary material, which is available to authorized users.

A Bayesian inference method for the analysis of transcriptional regulatory networks in metagenomic data

Background

Metagenomics enables the analysis of bacterial population composition and the study of emergent population features, such as shared metabolic pathways. Recently, we have shown that metagenomics datasets can be leveraged to characterize population-wide transcriptional regulatory networks, or meta-regulons, providing insights into how bacterial populations respond collectively to specific triggers. Here we formalize a Bayesian inference framework to analyze the composition of transcriptional regulatory networks in metagenomes by determining the probability of regulation of orthologous gene sequences. We assess the performance of this approach on synthetic datasets and we validate it by analyzing the copper-homeostasis network of Firmicutes species in the human gut microbiome.

Results

Assessment on synthetic datasets shows that our method provides a robust and interpretable metric for assessing putative regulation by a transcription factor on sets of promoter sequences mapping to an orthologous gene cluster. The inference framework integrates the regulatory contribution of secondary sites and can discern false positives arising from multiple instances of a clonal sequence. Posterior probabilities for orthologous gene clusters decline sharply when less than 20 % of mapped promoters have binding sites, but we introduce a sensitivity adjustment procedure to speed up computation that enhances regulation assessment in heterogeneous ortholog clusters. Analysis of the copper-homeostasis regulon governed by CsoR in the human gut microbiome Firmicutes reveals that CsoR controls itself and copper-translocating P-type ATPases, but not CopZ-type copper chaperones. Our analysis also indicates that CsoR frequently targets promoters with dual CsoR-binding sites, suggesting that it exploits higher-order binding conformations to fine-tune its activity.

Conclusions

We introduce and validate a method for the analysis of transcriptional regulatory networks from metagenomic data that enables inference of meta-regulons in a systematic and interpretable way. Validation of this method on the CsoR meta-regulon of gut microbiome Firmicutes illustrates the usefulness of the approach, revealing novel properties of the copper-homeostasis network in poorly characterized bacterial species and putting forward evidence of new mechanisms of DNA binding for this transcriptional regulator. Our approach will enable the comparative analysis of regulatory networks across metagenomes, yielding novel insights into the evolution of transcriptional regulatory networks.

Electronic supplementary material

The online version of this article (doi:10.1186/s13015-016-0082-8) contains supplementary material, which is available to authorized users.

Computational analysis of riboswitch-based regulation

Advances in computational analysis of riboswitches in the last decade have contributed greatly to our understanding of riboswitch regulatory roles and mechanisms. Riboswitches were originally discovered as part of the sequence analysis of the 5'-untranslated region of mRNAs in the hope of finding novel gene regulatory sites, and the existence of structural RNAs appeared to be a spurious phenomenon. As more riboswitches were discovered, they illustrated the diversity and adaptability of these RNA regulatory sequences. The fact that a chemically monotonous molecule like RNA can discern a wide range of substrates and exert a variety of regulatory mechanisms was subsequently demonstrated in diverse genomes and has hastened the development of sophisticated algorithms for their analysis and prediction. In this review, we focus on some of the computational tools for riboswitch detection and secondary structure prediction. The study of this simple yet efficient form of gene regulation promises to provide a more complete picture of a world that RNA once dominated and allows rational design of artificial riboswitches. This article is part of a Special Issue entitled: Riboswitches.

Functional characterization of WalRK: A two-component signal transduction system from Bacillus anthracis

Two-component signal transduction systems (TCS), consisting of a sensor histidine protein kinase and its cognate response regulator, are an important mode of environmental sensing in bacteria. Additionally, they have been found to regulate virulence determinants in several pathogens. Bacillus anthracis, the causative agent of anthrax and a bioterrorism agent, harbours 41 pairs of TCS. However, their role in its pathogenicity has remained largely unexplored. Here, we show that WalRK of B. anthracis forms a functional TCS which exhibits some species-specific functions. Biochemical studies showed that domain variants of WalK, the histidine kinase, exhibit classical properties of autophosphorylation and phosphotransfer to its cognate response regulator WalR. Interestingly, these domain variants also show phosphatase activity towards phosphorylated WalR, thereby making WalK a bifunctional histidine kinase/phosphatase. An in silico regulon determination approach, using a consensus binding sequence from Bacillus subtilis, provided a list of 30 genes that could form a putative WalR regulon in B. anthracis. Further, electrophoretic mobility shift assay was used to show direct binding of purified WalR to the upstream regions of three putative regulon candidates, an S-layer protein EA1, a cell division ABC transporter FtsE and a sporulation histidine kinase KinB3. Our work lends insight into the species-specific functions and mode of action of B. anthracis WalRK.

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WalRK forms a functional TCS in B. anthracis, expressed throughout the growth phase.

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WalK variants exhibit autophosphorylation and phosphotransfer to WalR.

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WalKc variants also show phosphatase activity towards phosphorylated WalR.

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A potential WalR regulon in B. anthracis was predicted in silico.

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DNA binding ability was demonstrated for WalR.