Massively Parallel Interrogation of the Effects of Gene Expression Levels on Fitness.

Data of gene expression levels across individuals, cell types, and disease states is expanding, yet our understanding of how expression levels impact phenotype is limited. Here, we present a massively parallel system for assaying the effect of gene expression levels on fitness in Saccharomyces cerevisiae by systematically altering the expression level of ∼100 genes at ∼100 distinct levels spanning a 500-fold range at high resolution. We show that the relationship between expression levels and growth is gene and environment specific and provides information on the function, stoichiometry, and interactions of genes. Wild-type expression levels in some conditions are not optimal for growth, and genes whose fitness is greatly affected by small changes in expression level tend to exhibit lower cell-to-cell variability in expression. Our study addresses a fundamental gap in understanding the functional significance of gene expression regulation and offers a framework for evaluating the phenotypic effects of expression variation.

Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP.

RNA transcripts are subject to posttranscriptional gene regulation involving hundreds of RNA-binding proteins (RBPs) and microRNA-containing ribonucleoprotein complexes (miRNPs) expressed in a cell-type dependent fashion. We developed a cell-based crosslinking approach to determine at high resolution and transcriptome-wide the binding sites of cellular RBPs and miRNPs. The crosslinked sites are revealed by thymidine to cytidine transitions in the cDNAs prepared from immunopurified RNPs of 4-thiouridine-treated cells. We determined the binding sites and regulatory consequences for several intensely studied RBPs and miRNPs, including PUM2, QKI, IGF2BP1-3, AGO/EIF2C1-4 and TNRC6A-C. Our study revealed that these factors bind thousands of sites containing defined sequence motifs and have distinct preferences for exonic versus intronic or coding versus untranslated transcript regions. The precise mapping of binding sites across the transcriptome will be critical to the interpretation of the rapidly emerging data on genetic variation between individuals and how these variations contribute to complex genetic diseases.

Microscopy-based phenotypic monitoring of MDA-MB-231 spheroids allows the evaluation of phenotype-directed therapy.

Breast cancer (BC) is the most commonly diagnosed cancer among women. Prognosis has improved over the years, to a large extent, owing to personalized therapy informed by molecular profiling of hormone receptors. However, there is a need for new therapeutic approaches for a subgroup of BCs lacking molecular markers, the Triple Negative Breast Cancer (TNBC) subgroup. TNBC is the most aggressive type of BC, lacks an effective standard of care, shows high levels of resistance and relapse is often inevitable. High resistance to therapy has been hypothesized to be associated with high intratumoral phenotypic heterogeneity. To characterize and treat this phenotypic heterogeneity, we optimized a whole-mount staining and image analysis protocol for three-dimensions (3D) spheroids. Applying this protocol to TNBC spheroids located in the outer region of the spheroid the cells with selected phenotypes: dividing, migrating, and high mitochondrial mass phenotypes. To evaluate the relevance of phenotype-based targeting these cell populations were targeted with Paclitaxel, Trametinib, and Everolimus, respectively, in a dose-dependent manner. Single agents cannot specifically target all phenotypes at the same time. Therefore, we combined drugs that should target independent phenotype. With this rationale we observed that combining Trametinib and Everolimus achieves the highest cytotoxicity at lower doses from all the tested combinations. These findings suggest a rational approach to design treatments can be evaluated in spheroids prior to pre-clinical models and potentially reduce adverse effects.

Controls for Phylogeny and Robust Analysis in Pareto Task Inference.

Understanding the tradeoffs faced by organisms is a major goal of evolutionary biology. One of the main approaches for identifying these tradeoffs is Pareto task inference (ParTI). Two recent papers claim that results obtained in ParTI studies are spurious due to phylogenetic dependence (Mikami T, Iwasaki W. 2021. The flipping t-ratio test: phylogenetically informed assessment of the Pareto theory for phenotypic evolution. Methods Ecol Evol. 12(4):696-706) or hypothetical p-hacking and population-structure concerns (Sun M, Zhang J. 2021. Rampant false detection of adaptive phenotypic optimization by ParTI-based Pareto front inference. Mol Biol Evol. 38(4):1653-1664). Here, we show that these claims are baseless. We present a new method to control for phylogenetic dependence, called SibSwap, and show that published ParTI inference is robust to phylogenetic dependence. We show how researchers avoided p-hacking by testing for the robustness of preprocessing choices. We also provide new methods to control for population structure and detail the experimental tests of ParTI in systems ranging from ammonites to cancer gene expression. The methods presented here may help to improve future ParTI studies.

Identification and consequences of miRNA-target interactions--beyond repression of gene expression.

Comparative genomics analyses and high-throughput experimental studies indicate that a microRNA (miRNA) binds to hundreds of sites across the transcriptome. Although the knockout of components of the miRNA biogenesis pathway has profound phenotypic consequences, most predicted miRNA targets undergo small changes at the mRNA and protein levels when the expression of the miRNA is perturbed. Alternatively, miRNAs can establish thresholds in and increase the coherence of the expression of their target genes, as well as reduce the cell-to-cell variability in target gene expression. Here, we review the recent progress in identifying miRNA targets and the emerging paradigms of how miRNAs shape the dynamics of target gene expression.

An active ß-lactamase is a part of an orchestrated cell wall stress resistance network of Bacillus subtilis and related rhizosphere species.

A hallmark of the Gram-positive bacteria, such as the soil-dwelling bacterium Bacillus subtilis, is their cell wall. Here, we report that d-leucine and flavomycin, biofilm inhibitors targeting the cell wall, activate the ß-lactamase PenP. This ß-lactamase contributes to ampicillin resistance in B. subtilis under all conditions tested. In contrast, both Spo0A, a master regulator of nutritional stress, and the general cell wall stress response, differentially contribute to ß-lactam resistance under different conditions. To test whether ß-lactam resistance and ß-lactamase genes are widespread in other Bacilli, we isolated Bacillus species from undisturbed soils, and found that their genomes can encode up to five ß-lactamases with differentiated activity spectra. Surprisingly, the activity of environmental ß-lactamases and PenP, as well as the general stress response, resulted in a similarly reduced lag phase of the culture in the presence of ß-lactam antibiotics, with little or no impact on the logarithmic growth rate. The length of the lag phase may determine the outcome of the competition between ß-lactams and ß-lactamases producers. Overall, our work suggests that antibiotic resistance genes in B. subtilis and related species are ancient and widespread, and could be selected by interspecies competition in undisturbed soils.

Inferring biological tasks using Pareto analysis of high-dimensional data.

We present the Pareto task inference method (ParTI; http://www.weizmann.ac.il/mcb/UriAlon/download/ParTI) for inferring biological tasks from high-dimensional biological data. Data are described as a polytope, and features maximally enriched closest to the vertices (or archetypes) allow identification of the tasks the vertices represent. We demonstrate that human breast tumors and mouse tissues are well described by tetrahedrons in gene expression space, with specific tumor types and biological functions enriched at each of the vertices, suggesting four key tasks.

MicroRNAs 103 and 107 regulate insulin sensitivity.

Defects in insulin signalling are among the most common and earliest defects that predispose an individual to the development of type 2 diabetes. MicroRNAs have been identified as a new class of regulatory molecules that influence many biological functions, including metabolism. However, the direct regulation of insulin sensitivity by microRNAs in vivo has not been demonstrated. Here we show that the expression of microRNAs 103 and 107 (miR-103/107) is upregulated in obese mice. Silencing of miR-103/107 leads to improved glucose homeostasis and insulin sensitivity. In contrast, gain of miR-103/107 function in either liver or fat is sufficient to induce impaired glucose homeostasis. We identify caveolin-1, a critical regulator of the insulin receptor, as a direct target gene of miR-103/107. We demonstrate that caveolin-1 is upregulated upon miR-103/107 inactivation in adipocytes and that this is concomitant with stabilization of the insulin receptor, enhanced insulin signalling, decreased adipocyte size and enhanced insulin-stimulated glucose uptake. These findings demonstrate the central importance of miR-103/107 to insulin sensitivity and identify a new target for the treatment of type 2 diabetes and obesity.

miR-184 Regulates Pancreatic ß-Cell Function According to Glucose Metabolism.

In response to fasting or hyperglycemia, the pancreatic ß-cell alters its output of secreted insulin; however, the pathways governing this adaptive response are not entirely established. Although the precise role of microRNAs (miRNAs) is also unclear, a recurring theme emphasizes their function in cellular stress responses. We recently showed that miR-184, an abundant miRNA in the ß-cell, regulates compensatory proliferation and secretion during insulin resistance. Consistent with previous studies showing miR-184 suppresses insulin release, expression of this miRNA was increased in islets after fasting, demonstrating an active role in the ß-cell as glucose levels lower and the insulin demand ceases. Additionally, miR-184 was negatively regulated upon the administration of a sucrose-rich diet in Drosophila, demonstrating strong conservation of this pathway through evolution. Furthermore, miR-184 and its target Argonaute2 remained inversely correlated as concentrations of extracellular glucose increased, underlining a functional relationship between this miRNA and its targets. Lastly, restoration of Argonaute2 in the presence of miR-184 rescued suppression of miR-375-targeted genes, suggesting these genes act in a coordinated manner during changes in the metabolic context. Together, these results highlight the adaptive role of miR-184 according to glucose metabolism and suggest the regulatory role of this miRNA in energy homeostasis is highly conserved.

Analysis of CDS-located miRNA target sites suggests that they can effectively inhibit translation.

Most of what is presently known about how miRNAs regulate gene expression comes from studies that characterized the regulatory effect of miRNA binding sites located in the 3' untranslated regions (UTR) of mRNAs. In recent years, there has been increasing evidence that miRNAs also bind in the coding region (CDS), but the implication of these interactions remains obscure because they have a smaller impact on mRNA stability compared with miRNA-target interactions that involve 3' UTRs. Here we show that miRNA-complementary sites that are located in both CDS and 3'-UTRs are under selection pressure and share the same sequence and structure properties. Analyzing recently published data of ribosome-protected fragment profiles upon miRNA transfection from the perspective of the location of miRNA-complementary sites, we find that sites located in the CDS are most potent in inhibiting translation, while sites located in the 3' UTR are more efficient at triggering mRNA degradation. Our study suggests that miRNAs may combine targeting of CDS and 3' UTR to flexibly tune the time scale and magnitude of their post-transcriptional regulatory effects.

A biophysical miRNA-mRNA interaction model infers canonical and noncanonical targets.

We introduce a biophysical model of miRNA-target interaction and infer its parameters from Argonaute 2 cross-linking and immunoprecipitation data. We show that a substantial fraction of human miRNA target sites are noncanonical and that predicted target-site affinity correlates well with the extent of target destabilization. Our model provides a rigorous biophysical approach to miRNA target identification beyond ad hoc miRNA seed-based methods.

Geometry of the Gene Expression Space of Individual Cells.

There is a revolution in the ability to analyze gene expression of single cells in a tissue. To understand this data we must comprehend how cells are distributed in a high-dimensional gene expression space. One open question is whether cell types form discrete clusters or whether gene expression forms a continuum of states. If such a continuum exists, what is its geometry? Recent theory on evolutionary trade-offs suggests that cells that need to perform multiple tasks are arranged in a polygon or polyhedron (line, triangle, tetrahedron and so on, generally called polytopes) in gene expression space, whose vertices are the expression profiles optimal for each task. Here, we analyze single-cell data from human and mouse tissues profiled using a variety of single-cell technologies. We fit the data to shapes with different numbers of vertices, compute their statistical significance, and infer their tasks. We find cases in which single cells fill out a continuum of expression states within a polyhedron. This occurs in intestinal progenitor cells, which fill out a tetrahedron in gene expression space. The four vertices of this tetrahedron are each enriched with genes for a specific task related to stemness and early differentiation. A polyhedral continuum of states is also found in spleen dendritic cells, known to perform multiple immune tasks: cells fill out a tetrahedron whose vertices correspond to key tasks related to maturation, pathogen sensing and communication with lymphocytes. A mixture of continuum-like distributions and discrete clusters is found in other cell types, including bone marrow and differentiated intestinal crypt cells. This approach can be used to understand the geometry and biological tasks of a wide range of single-cell datasets. The present results suggest that the concept of cell type may be expanded. In addition to discreet clusters in gene-expression space, we suggest a new possibility: a continuum of states within a polyhedron, in which the vertices represent specialists at key tasks.

MicroRNA binding sites in the coding region of mRNAs: extending the repertoire of post-transcriptional gene regulation.

It is well established that microRNAs (miRNAs) induce mRNA degradation by binding to 3' untranslated regions (UTRs). The functionality of sites in the coding domain sequence (CDS), on the other hand, remains under discussion. Such sites have limited impact on target mRNA abundance and recent work suggests that miRNAs bind in the CDS to inhibit translation. What then could be the regulatory benefits of translation inhibition through CDS targeting compared to mRNA degradation following 3' UTR binding? We propose that these domain-dependent effects serve to diversify the functional repertoire of post-transcriptional gene expression control. Possible regulatory benefits may include tuning the time-scale and magnitude of post-transcriptional regulation, regulating protein abundance depending on or independently of the cellular state, and regulation of the protein abundance of alternative splice variants. Finally, we review emerging evidence that these ideas may generalize to RNA-binding proteins beyond miRNAs and Argonaute proteins.

Linear superposition and prediction of bacterial promoter activity dynamics in complex conditions.

Bacteria often face complex environments. We asked how gene expression in complex conditions relates to expression in simpler conditions. To address this, we obtained accurate promoter activity dynamical measurements on 94 genes in E. coli in environments made up of all possible combinations of four nutrients and stresses. We find that the dynamics across conditions is well described by two principal component curves specific to each promoter. As a result, the promoter activity dynamics in a combination of conditions is a weighted average of the dynamics in each condition alone. The weights tend to sum up to approximately one. This weighted-average property, called linear superposition, allows predicting the promoter activity dynamics in a combination of conditions based on measurements of pairs of conditions. If these findings apply more generally, they can vastly reduce the number of experiments needed to understand how E. coli responds to the combinatorially huge space of possible environments.

A quantitative analysis of CLIP methods for identifying binding sites of RNA-binding proteins.

Cross-linking and immunoprecipitation (CLIP) is increasingly used to map transcriptome-wide binding sites of RNA-binding proteins. We developed a method for CLIP data analysis, and applied it to compare CLIP with photoactivatable ribonucleoside-enhanced CLIP (PAR-CLIP) and to uncover how differences in cross-linking and ribonuclease digestion affect the identified sites. We found only small differences in accuracies of these methods in identifying binding sites of HuR, which binds low-complexity sequences, and Argonaute 2, which has a complex binding specificity. We found that cross-link-induced mutations led to single-nucleotide resolution for both PAR-CLIP and CLIP. Our results confirm the expectation from original CLIP publications that RNA-binding proteins do not protect their binding sites sufficiently under the denaturing conditions used during the CLIP procedure, and we show that extensive digestion with sequence-specific RNases strongly biases the recovered binding sites. This bias can be substantially reduced by milder nuclease digestion conditions.

Timescales and bottlenecks in miRNA-dependent gene regulation.

MiRNAs are post-transcriptional regulators that contribute to the establishment and maintenance of gene expression patterns. Although their biogenesis and decay appear to be under complex control, the implications of miRNA expression dynamics for the processes that they regulate are not well understood. We derived a mathematical model of miRNA-mediated gene regulation, inferred its parameters from experimental data sets, and found that the model describes well time-dependent changes in mRNA, protein and ribosome density levels measured upon miRNA transfection and induction. The inferred parameters indicate that the timescale of miRNA-dependent regulation is slower than initially thought. Delays in miRNA loading into Argonaute proteins and the slow decay of proteins relative to mRNAs can explain the typically small changes in protein levels observed upon miRNA transfection. For miRNAs to regulate protein expression on the timescale of a day, as miRNAs involved in cell-cycle regulation do, accelerated miRNA turnover is necessary.

Microenvironmental reorganization in brain tumors following radiotherapy and recurrence revealed by hyperplexed immunofluorescence imaging.

The tumor microenvironment plays a crucial role in determining response to treatment. This involves a series of interconnected changes in the cellular landscape, spatial organization, and extracellular matrix composition. However, assessing these alterations simultaneously is challenging from a spatial perspective, due to the limitations of current high-dimensional imaging techniques and the extent of intratumoral heterogeneity over large lesion areas. In this study, we introduce a spatial proteomic workflow termed Hyperplexed Immunofluorescence Imaging (HIFI) that overcomes these limitations. HIFI allows for the simultaneous analysis of > 45 markers in fragile tissue sections at high magnification, using a cost-effective high-throughput workflow. We integrate HIFI with machine learning feature detection, graph-based network analysis, and cluster-based neighborhood analysis to analyze the microenvironment response to radiation therapy in a preclinical model of glioblastoma, and compare this response to a mouse model of breast-to-brain metastasis. Here we show that glioblastomas undergo extensive spatial reorganization of immune cell populations and structural architecture in response to treatment, while brain metastases show no comparable reorganization. Our integrated spatial analyses reveal highly divergent responses to radiation therapy between brain tumor models, despite equivalent radiotherapy benefit.

Kaposi's sarcoma herpesvirus microRNAs target caspase 3 and regulate apoptosis.

Kaposi's sarcoma herpesvirus (KSHV) encodes a cluster of twelve micro (mi)RNAs, which are abundantly expressed during both latent and lytic infection. Previous studies reported that KSHV is able to inhibit apoptosis during latent infection; we thus tested the involvement of viral miRNAs in this process. We found that both HEK293 epithelial cells and DG75 cells stably expressing KSHV miRNAs were protected from apoptosis. Potential cellular targets that were significantly down-regulated upon KSHV miRNAs expression were identified by microarray profiling. Among them, we validated by luciferase reporter assays, quantitative PCR and western blotting caspase 3 (Casp3), a critical factor for the control of apoptosis. Using site-directed mutagenesis, we found that three KSHV miRNAs, miR-K12-1, 3 and 4-3p, were responsible for the targeting of Casp3. Specific inhibition of these miRNAs in KSHV-infected cells resulted in increased expression levels of endogenous Casp3 and enhanced apoptosis. Altogether, our results suggest that KSHV miRNAs directly participate in the previously reported inhibition of apoptosis by the virus, and are thus likely to play a role in KSHV-induced oncogenesis.

MicroRNA-194 is a target of transcription factor 1 (Tcf1, HNF1α) in adult liver and controls expression of frizzled-6.

UNLABELLED: Transcription factor 1 (Tcf1; hepatocyte nuclear factor 1α [HNF1α]) is critical for hepatocyte development and function. Whether Tcf1 also regulates hepatic microRNAs (miRNAs) has not been investigated yet. Here we analyzed Tcf1-dependent miRNA expression in adult mice in which this transcription factor had been genetically deleted (Tcf1(-/-) ) using miRNA microarray analysis. The miR-192/-194 cluster was markedly down-regulated in liver of Tcf1(-/-) mice. MiR-192/-194 levels were also decreased in two other tissues that express Tcf1, kidney and small intestine, although to a lesser extent than in liver. In order to identify targets of miR-192/-194 in vivo we combined Affymetrix gene analysis of liver in which miR-192/-194 had been silenced or overexpressed, respectively, and tested regulated messenger RNAs (mRNAs) with multiple binding sites for these miRNAs. This approach revealed frizzled-6 (Fzd6) as a robust endogenous target of miR-194. MiR-194 also targets human FZD6 and expression of miR-194 and Fzd6 are inversely correlated in a mouse model of hepatocellular carcinoma (Dgcr8(flox/flox) p53(flox/flox) × Alb-Cre). CONCLUSION: Our results support a role of miR-194 in liver tumorigenesis through its endogenous target Fzd6. These results may have important implications for Tcf1-mediated liver proliferation.

Argonaute CLIP--a method to identify in vivo targets of miRNAs.

microRNAs are important regulators of gene expression that guide translational repression and degradation of target mRNAs. Only relatively few miRNA targets have been characterized, and computational prediction is hampered by the relatively small number of nucleotides that seem to be involved in target recognition. Argonaute (Ago) crosslinking and immunoprecipitation (CLIP) in combination with next-generation sequencing proved to be a successful method for identifying targets of endogenous cellular miRNAs on a transcriptome-wide scale. Here we review various approaches to Ago CLIP, describe in detail the PAR-CLIP method and provide an outline of the necessary computational analysis for identification of in vivo miRNA binding sites.