Posttranscriptional expression regulation: what determines translation rates?

Prognostic value of Maspin protein level in patients with triple negative breast cancer

The search for prognostic markers in breast cancer has bumped into a typical feature of these tumors, intra and intertumoral heterogeneity. Changes in the expression profile, localization of these proteins or shedding to the surrounding stroma can be useful in the search for new markers. In this context, classification by molecular subtypes can bring perspectives for both diagnosis and screening for appropriate treatments. However, the Triple Negative (TN) subtype, which is already the one with the worst prognosis, lacks appropriate and consistent molecular markers. In this work, we analyzed 346 human breast cancer samples in tissue microarrays (TMA) from cases diagnosed with invasive breast carcinoma to assess the expression and localization pattern of Maspin and their correlation with clinical parameters. To complement our findings, we also used TCGA data to analyze the mRNA levels of these respective genes. Our data suggests that the TN subtype demonstrates a higher level of cytoplasmic Maspin compared to the other subtypes. Maspin transcript levels follow the same trend. However, TN patients with lower Maspin expression tend to have worse overall survival and free-survival metastasis rates. Finally, we used Maspin expression data to verify possible relationships with the clinicopathological information of our cohort. Our univariate analyses indicate that Maspin is related to the expression of estrogen receptor (ER) and progesterone receptor (PR). Furthermore, Maspin expression levels also showed correlation with Scarff-Bloom-Richardson (SBR) parameter, and stromal Maspin showed a relationship with lymph node involvement. Our data is not consistently robust enough to categorize Maspin as a prognostic marker. However, it does indicate a change in the expression profile within the TN subtype.

Increased seawater temperature triggers thermal, oxidative and metabolic response of Ostrea edulis, leading to anaerobiosis

Bivalves are among the marine organisms most influenced by climate change. Despite the flat oyster's Ostrea edulis high economic value, its culture is developed on a very small scale, since this species possesses a strong susceptibility to abiotic stressors. Due to climate change, temperature is one of the most critical environmental parameters for the welfare of the Mediterranean basin's marine inhabitants. The present study's purpose was to investigate the physiological performance of the Mediterranean's native O. edulis as it faces exposure to different temperatures. Since juveniles are more susceptible to abiotic stressors, this experimental procedure was focused on young individuals. The seawater temperatures studied included a standard control temperature of 21 °C (often observed in several marine areas throughout the Mediterranean), as well as increased seawater temperatures of 25 °C and 28 °C, occasionally occurring in shallow Mediterranean waters inhabited by bivalve spat. These were selected since the tissues of O. edulis becomes partly anaerobic in temperatures exceeding 26 °C, while cardiac dysfunction (arrhythmia) emerges at 28 °C. The results demonstrate that temperatures above 25 °C trigger both the transcriptional upregulation of hsp70 and hsp90, and the antioxidant genes Cu/Zn sod and catalase. Enhancement of thermal tolerance and increased defense against increased ROS production during thermal stress, were observed. As the intensity and duration of thermal stress increases, apoptotic damage may also occur. The increased oxidative and thermal stress incurred at the highest temperature of 28 °C, seemed to trigger the switch from aerobic to anaerobic metabolism, reflected by higher pepck mRNA expressions and lower ETS activity.

Schlafen14 Impairs HIV-1 Expression in a Codon Usage-Dependent Manner

Schlafen (SLFN) is a family of proteins upregulated by type I interferons with a regulatory role in translation. Intriguingly, SLFN14 associates with the ribosome and can degrade rRNA, tRNA, and mRNA in vitro, but a role in translation is still unknown. Ribosomes are important regulatory hubs during translation elongation of mRNAs rich in rare codons. Therefore, we evaluated the potential role of SLFN14 in the expression of mRNAs enriched in rare codons, using HIV-1 genes as a model. We found that, in a variety of cell types, including primary immune cells, SLFN14 regulates the expression of HIV-1 and non-viral genes based on their codon adaptation index, a measurement of the synonymous codon usage bias; consequently, SLFN14 inhibits the replication of HIV-1. The potent inhibitory effect of SLFN14 on the expression of the rare codon-rich transcript HIV-1 Gag was minimized by codon optimization. Mechanistically, we found that the endoribonuclease activity of SLFN14 is required, and that ribosomal RNA degradation is involved. Therefore, we propose that SLFN14 impairs the expression of HIV-1 transcripts rich in rare codons, in a catalytic-dependent manner.

Emerging Prognostic and Predictive Significance of Stress Keratin 17 in HPV-Associated and Non HPV-Associated Human Cancers: A Scoping Review

A growing body of literature suggests that the expression of cytokeratin 17 (K17) correlates with inferior clinical outcomes across various cancer types. In this scoping review, we aimed to review and map the available clinical evidence of the prognostic and predictive value of K17 in human cancers. PubMed, Web of Science, Embase (via Scopus), Cochrane Central Register of Controlled Trials, and Google Scholar were searched for studies of K17 expression in human cancers. Eligible studies were peer-reviewed, published in English, presented original data, and directly evaluated the association between K17 and clinical outcomes in human cancers. Of the 1705 studies identified in our search, 58 studies met criteria for inclusion. Studies assessed the prognostic significance (n = 54), predictive significance (n = 2), or both the prognostic and predictive significance (n = 2). Altogether, 11 studies (19.0%) investigated the clinical relevance of K17 in cancers with a known etiologic association to HPV; of those, 8 (13.8%) were focused on head and neck squamous cell carcinoma (HNSCC), and 3 (5.1%) were focused on cervical squamous cell carcinoma (SCC). To date, HNSCC, as well as triple-negative breast cancer (TNBC) and pancreatic cancer, were the most frequently studied cancer types. K17 had prognostic significance in 16/17 investigated cancer types and 43/56 studies. Our analysis suggests that K17 is a negative prognostic factor in the majority of studied cancer types, including HPV-associated types such as HNSCC and cervical cancer (13/17), and a positive prognostic factor in 2/17 studied cancer types (urothelial carcinoma of the upper urinary tract and breast cancer). In three out of four predictive studies, K17 was a negative predictive factor for chemotherapy and immune checkpoint blockade therapy response.

Multi-omics reveals largely distinct transcript- and protein-level responses to the environment in an intertidal mussel

Organismal responses to stressful environments are influenced by numerous transcript- and protein-level mechanisms, and the relationships between expression changes at these levels are not always straightforward. Here, we used paired transcriptomic and proteomic datasets from two previous studies from gill of the California mussel, Mytilus californianus, to explore how simultaneous transcript and protein abundance patterns may diverge under different environmental scenarios. Field-acclimatized mussels were sampled from two disparate intertidal sites; individuals from one site were subjected to three further treatments (common garden, low-intertidal or high-intertidal outplant) that vary in temperature and feeding time. Assessing 1519 genes shared between the two datasets revealed that both transcript and protein expression patterns differentiated the treatments at a global level, despite numerous underlying discrepancies. There were far more instances of differential expression between treatments in transcript only (1451) or protein only (226) than of the two levels shifting expression concordantly (68 instances). Upregulated expression of cilium-associated transcripts (likely related to feeding) was associated with relatively benign field treatments. In the most stressful treatment, transcripts, but not proteins, for several molecular chaperones (including heat shock proteins and endoplasmic reticulum chaperones) were more abundant, consistent with a threshold model for induction of translation of constitutively available mRNAs. Overall, these results suggest that the relative importance of transcript- and protein-level regulation (translation and/or turnover) differs among cellular functions and across specific microhabitats or environmental contexts. Furthermore, the degree of concordance between transcript and protein expression can vary across benign versus acutely stressful environmental conditions.

Investigation of the highly endangered Pinna nobilis' mass mortalities: Seasonal and temperature patterns of health status, antioxidant and heat stress responses

Recently, P. nobilis populations have suffered a tremendous reduction, with pathogens potentially playing a crucial role. Considering its highly endangered status, mechanisms leading to mass mortalities were examined in one or multiple pathogens infected populations. Thus, seasonal antioxidant enzymatic activities, hsp70 and catalase mRNA levels, were investigated in two different Greek populations, during mass mortality events in summer of 2020. Samples were collected from Fthiotis and Lesvos during February (T^oC 14 ± 1.2 and 15 ± 1 respectively), April (T^oC 18 ± 1.2 and 17 ± 1.3 respectively), and June (T^oC 24.5 ± 1.5 and 21.5 ± 1.5 respectively) 2020. In July of the same year (T^oC 26.5 ± 1.7 in Fthiotis and 24.5 ± 1.7 in Lesvos), no live specimens were found. All biochemical parameters and phylogenetic analysis suggest that pathogen infection increases P. nobilis sensitivity to water temperature, subsequently leading to mass mortality. The latter was obvious in Fthiotis individuals, in which Haplosporidium pinnae was also observed with Mycobacterium spp., compared to Lesvos individuals.

The impact of ascidian biofouling on the farmed Mediterranean mussel Mytilus galloprovincialis physiology and welfare, revealed by stress biomarkers

In biofouling communities, ascidians are among the most damaging species, presenting severe threats, such as depressed growth rates and decreased chances of lower survival, to shellfish aquaculture. However, little is known concerning the fouled shellfish physiology. In an effort to obtain information for the magnitude of stress caused by ascidians to farmed Mytilus galloprovincialis, five seasonal samplings took place in a mussel aquaculture farm suffering from ascidian biofoulants, in Vistonicos Bay, Greece. The dominant ascidian species were recorded and several stress biomarkers, including Hsp gene expression at both mRNA and protein levels, as well as MAPKs levels, and enzymatic activities of intermediate metabolism were examined. Almost all investigated biomarkers revealed elevated stress levels in fouled mussels compared to non-fouled. This enhanced physiological stress seems to be season-independent and can be attributed to the oxidative stress and/or feed deprivation caused by ascidian biofouling, thus illuminating the biological impact of this phenomenon.

A dynamical stochastic model of yeast translation across the cell cycle

Translation is a central step in gene expression, however its quantitative and time-resolved regulation is poorly understood. We developed a discrete, stochastic model for protein translation in S. cerevisiae in a whole-transcriptome, single-cell context. A "base case" scenario representing an average cell highlights translation initiation rates as the main co-translational regulatory parameters. Codon usage bias emerges as a secondary regulatory mechanism through ribosome stalling. Demand for anticodons with low abundancy is shown to cause above-average ribosome dwelling times. Codon usage bias correlates strongly both with protein synthesis rates and elongation rates. Applying the model to a time-resolved transcriptome estimated by combining data from FISH and RNA-Seq experiments, it could be shown that increased total transcript abundance during the cell cycle decreases translation efficiency at single transcript level. Translation efficiency grouped by gene function shows highest values for ribosomal and glycolytic genes. Ribosomal proteins peak in S phase while glycolytic proteins rank highest in later cell cycle phases.

"Less is more": a dose-response account of intranasal oxytocin pharmacodynamics in the human brain

Intranasal oxytocin is attracting attention as a potential treatment for several brain disorders due to promising preclinical results. However, translating findings to humans has been hampered by remaining uncertainties about its pharmacodynamics and the methods used to probe its effects in the human brain. Using a dose-response design (9, 18 and 36 IU), we demonstrate that intranasal oxytocin-induced changes in local regional cerebral blood flow (rCBF) in the amygdala at rest, and in the covariance between rCBF in the amygdala and other key hubs of the brain oxytocin system, follow a dose-response curve with maximal effects for lower doses. Yet, the effects on local rCBF might vary by amygdala subdivision, highlighting the need to qualify dose-response curves within subregion. We further link physiological changes with the density of the oxytocin receptor gene mRNA across brain regions, strengthening our confidence in intranasal oxytocin as a valid approach to engage central targets. Finally, we demonstrate that intranasal oxytocin does not disrupt cerebrovascular reactivity, which corroborates the validity of haemodynamic neuroimaging to probe the effects of intranasal oxytocin in the human brain. DATA AVAILABILITY: Participants did not consent for open sharing of the data. Therefore, data can only be accessed from the corresponding author upon reasonable request.

Exploration and characterization of hypoxia-inducible endogenous promoters in Aspergillus niger

Aspergillus niger is widely used for the efficient production of organic acids and enzyme preparations. However, this organism lacks basic genetic elements for dynamic control, especially inducible promoters that can respond to specific environmental signals. Since these are desirable for better adaptation of fermentation to large-scale industrial production, herein, we have identified the two first hypoxia-inducible promoters in A. niger, PsrbB and PfhbA. Their performance under high or low oxygen conditions was monitored using two reporter proteins, green fluorescent protein (EGFP) and β-glucuronidase (GUS). For comparison, basal expression of the general strong promoter PgpdA was lower than PsrbB but higher than PfhbA. However, under hypoxia, both promoters showed higher expression than under hyperoxia, and these values were also higher than those observed for PgpdA. For PsrbB, strength under hypoxia was ~2-3 times higher than under hyperoxia (for PfhbA, 3-9 times higher) and ~2.5-5 times higher than for PgpdA (for PfhbA, 2-3 times higher). Promoter truncation analysis showed that the PsrbB fragment -1024 to -588 bp is the core region that determines hypoxia response. KEY POINTS: The first identification of two hypoxia-inducible promoters in A. niger is a promising tool for modulation of target genes under hypoxia. Two reporter genes revealed a different activity and responsiveness to hypoxia of PfhbA and PsrbB promoters, which is relevant for the development of dynamic metabolic regulation of A. niger fermentation. PsrbB promoter truncation and bioinformatics analysis is the foundation for further research.

The extracellular matrix protein Agrin is expressed by osteoblasts and contributes to their differentiation

The extracellular matrix protein Agrin has been detected in chondrocytes and endosteal osteoblasts but its function in osteoblast differentiation has not been investigated yet. Thus, it is possible that Agrin contributes to osteoblast differentiation and, due to Agrin and wingless-related integration site (Wnt) sharing the same receptor, transmembrane low-density lipoprotein receptor-related protein 4 (Lrp4), and the crosstalk between Wnt and bone morphogenetic protein (BMP) signalling, both pathways could be involved in this Agrin-mediated osteoblast differentiation. Confirming this, Agrin and its receptors Lrp4 and α-dystroglycan (Dag1) were expressed during differentiation of osteoblasts from three different sources. Moreover, the disruption of Agrin impaired the expression of its receptors and osteoblast differentiation, and the treatment with recombinant Agrin slightly increase this process. In addition, whilst Agrin knockdown downregulated the expression of genes related to Wnt and BMP signalling pathways, the addition of Agrin had no effect on these genes. Altogether, these data uncover the contribution of Agrin to osteoblast differentiation and suggest that, at least in part, an Agrin-Wnt-BMP circuit is involved in this process. This makes Agrin a candidate as target for developing new therapeutic strategies to treat bone-related diseases and injuries.

Erosion of human X chromosome inactivation causes major remodeling of the iPSC proteome

X chromosome inactivation (XCI) is a dosage compensation mechanism in female mammals whereby transcription from one X chromosome is repressed. Analysis of human induced pluripotent stem cells (iPSCs) derived from female donors identified that low levels of XIST RNA correlated strongly with erosion of XCI. Proteomic analysis, RNA sequencing (RNA-seq), and polysome profiling showed that XCI erosion resulted in amplified RNA and protein expression from X-linked genes, providing a proteomic characterization of skewed dosage compensation. Increased protein expression was also detected from autosomal genes without an mRNA increase, thus altering the protein-RNA correlation between the X chromosome and autosomes. XCI-eroded lines display an ∼13% increase in total cell protein content, with increased ribosomal proteins, ribosome biogenesis and translation factors, and polysome levels. We conclude that XCI erosion in iPSCs causes a remodeling of the proteome, affecting the expression of a much wider range of proteins and disease-linked loci than previously realized.

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iPSCs with eroded XCI show defective dosage compensation at the protein level

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iPSCs with eroded XCI display elevated total protein content

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iPSCs with eroded XCI show increased ribosome and polysome levels

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Eroded XCI increases protein but not mRNA expression for 21% of autosomal genes

The human-specific duplicated α7 gene inhibits the ancestral α7, negatively regulating nicotinic acetylcholine receptor-mediated transmitter release

Gene duplication generates new functions and traits, enabling evolution. Human-specific duplicated genes in particular are primary sources of innovation during our evolution although they have very few known functions. Here we examine the brain function of one of these genes (CHRFAM7A) and its product (dupα7 subunit). This gene results from a partial duplication of the ancestral CHRNA7 gene encoding the α7 subunit that forms the homopentameric α7 nicotinic acetylcholine receptor (α7-nAChR). The functions of α7-nAChR in the brain are well defined, including the modulation of synaptic transmission and plasticity underlying normal attention, cognition, learning, and memory processes. However, the role of the dupα7 subunit remains unexplored at the neuronal level. Here, we characterize that role by combining immunoblotting, quantitative RT-PCR and FRET techniques with functional assays of α7-nAChR activity using human neuroblastoma SH-SY5Y cell variants with different dupα7 expression levels. Our findings reveal a physical interaction between dupα7 and α7 subunits in fluorescent protein-tagged dupα7/α7 transfected cells that negatively affects normal α7-nAChR activity. Specifically, in both single cells and cell populations, the [Ca²⁺]_i signal and the exocytotic response induced by selective stimulation of α7-nAChR were either significantly inhibited by stable dupα7 overexpression or augmented after silencing dupα7 gene expression with specific siRNAs. These findings identify a new role for the dupα7 subunit as a negative regulator of α7-nAChR-mediated control of exocytotic neurotransmitter release. If this effect is excessive, it would result in an impaired synaptic transmission that could underlie the neurocognitive and neuropsychiatric disorders associated with α7-nAChR dysfunction.

A Modelling Framework Linking Resource-Based Stochastic Translation to the Optimal Design of Synthetic Constructs

Simple Summary

In synthetic biology, it is commonplace to design and insert gene expression constructs into cells for the production of useful proteins. In order to maximise production yield, it is useful to predict the performance of these “engineered cells” in advance of conducting experiments. This is typically a complex task, which in recent years has motivated the use of “whole-cell models” (WCMs) that act as computational tools for predicting different aspects of cell growth. Many useful WCMs exist, however a common problem is their over-simplification of ribosome movement on mRNA transcripts during translation. WCMs typically don’t consider that, for constructs with inefficient (“slow”) codons, ribosomes can stall and form “traffic jams”, thereby becoming unavailable for translation of other proteins. To more accurately address these scenarios, we have built a computational framework that combines whole-cell modelling with a detailed account of ribosome movement on mRNA. We show how our framework can be used to link the modular design of a gene expression construct (via its promoter, ribosome binding site and codon composition) to protein yield during continuous cell culture, with a particular focus on how the optimal design can change over time in the presence or absence of “slow” codons.

Abstract

The effect of gene expression burden on engineered cells has motivated the use of “whole-cell models” (WCMs) that use shared cellular resources to predict how unnatural gene expression affects cell growth. A common problem with many WCMs is their inability to capture translation in sufficient detail to consider the impact of ribosomal queue formation on mRNA transcripts. To address this, we have built a “stochastic cell calculator” (StoCellAtor) that combines a modified TASEP with a stochastic implementation of an existing WCM. We show how our framework can be used to link a synthetic construct’s modular design (promoter, ribosome binding site (RBS) and codon composition) to protein yield during continuous culture, with a particular focus on the effects of low-efficiency codons and their impact on ribosomal queues. Through our analysis, we recover design principles previously established in our work on burden-sensing strategies, namely that changing promoter strength is often a more efficient way to increase protein yield than RBS strength. Importantly, however, we show how these design implications can change depending on both the duration of protein expression, and on the presence of ribosomal queues.

Can ODE gene regulatory models neglect time lag or measurement scaling?

MOTIVATION

Many ordinary differential equation (ODE) models have been introduced to replace linear regression models for inferring gene regulatory relationships from time-course gene expression data. But, since the observed data are usually not direct measurements of the gene products or there is an unknown time lag in gene regulation, it is problematic to directly apply traditional ODE models or linear regression models.

RESULTS

We introduce a lagged ODE model to infer lagged gene regulatory relationships from time-course measurements, which are modeled as linear transformation of the gene products. A time-course microarray dataset from a yeast cell-cycle study is used for simulation assessment of the methods and real data analysis. The results show that our method, by considering both time lag and measurement scaling, performs much better than other linear and ODE models. It indicates the necessity of explicitly modeling the time lag and measurement scaling in ODE gene regulatory models.

AVAILABILITY AND IMPLEMENTATION

R code is available at https://www.sta.cuhk.edu.hk/xfan/share/lagODE.zip.

Differentiation of Human Mesenchymal Stem Cells from Wharton's Jelly Towards Neural Stem Cells Using A Feasible and Repeatable Protocol

The transplantation of neural stem cells (NSCs) capable of regenerating to the cells of the central nervous system (CNS) is a promising strategy in the treatment of CNS diseases and injury. As previous studies have highlighted mesenchymal stem cells (MSCs) as a source of NSCs, this study aimed to develop a feasible, efficient, and reproducible method for the neural induction of MSCs isolated from Wharton's jelly (hWJ-MSCs). We induced neural differentiation in a monolayer culture using epidermal growth factor, basic fibroblast growth factor, N2, and B27 supplements. This resulted in a homogenous population of proliferating cells that expressed certain neural markers at both the protein and mRNA levels. Flow cytometry and immunocytochemistry confirmed the expression of neural markers: nestin, sex-determining region Y (SRY) box 1 and 2 (SOX1 and SOX2), microtubule-associated protein 2 (MAP2), and glial fibrillary acidic protein (GFAP). The qRT-PCR analysis revealed significantly enhanced expression of nestin and MAP2 in differentiated cells. This study confirms that it is possible to generate NSCs-like cells from hWJ-MSCs in a 2D culture using a practical method. However, the therapeutic effectiveness of such differentiated cells should be extended to confirm the terminal differentiation ability and electrophysiological properties of neurons derived from them.

Analysis of essential gene dynamics under antibiotic stress in Streptococcus sanguinis

The paradoxical response of Streptococcus sanguinis to drugs prescribed for dental and clinical practices has complicated treatment guidelines and raised the need for further investigation. We conducted a high throughput study on concomitant transcriptome and proteome dynamics in a time course to assess S. sanguinis behaviour under a sub-inhibitory concentration of ampicillin. Temporal changes at the transcriptome and proteome level were monitored to cover essential genes and proteins over a physiological map of intricate pathways. Our findings revealed that translation was the functional category in S. sanguinis that was most enriched in essential proteins. Moreover, essential proteins in this category demonstrated the greatest conservation across 2774 bacterial proteomes, in comparison to other essential functional categories like cell wall biosynthesis and energy production. In comparison to non-essential proteins, essential proteins were less likely to contain ‘degradation-prone’ amino acids at their N-terminal position, suggesting a longer half-life. Despite the ampicillin-induced stress, the transcriptional up-regulation of amino acid-tRNA synthetases and proteomic elevation of amino acid biosynthesis enzymes favoured the enriched components of essential proteins revealing ‘proteomic signatures’ that can be used to bridge the genotype–phenotype gap of S. sanguinis under ampicillin stress. Furthermore, we identified a significant correlation between the levels of mRNA and protein for essential genes and detected essential protein-enriched pathways differentially regulated through a persistent stress response pattern at late time points. We propose that the current findings will help characterize a bacterial model to study the dynamics of essential genes and proteins under clinically relevant stress conditions.

Quantifying post-transcriptional regulation in the development of Drosophila melanogaster

Even though proteins are produced from mRNA, the correlation between mRNA levels and protein abundances is moderate in most studies, occasionally attributed to complex post-transcriptional regulation. To address this, we generate a paired transcriptome/proteome time course dataset with 14 time points during Drosophila embryogenesis. Despite a limited mRNA-protein correlation (ρ = 0.54), mathematical models describing protein translation and degradation explain 84% of protein time-courses based on the measured mRNA dynamics without assuming complex post transcriptional regulation, and allow for classification of most proteins into four distinct regulatory scenarios. By performing an in-depth characterization of the putatively post-transcriptionally regulated genes, we postulate that the RNA-binding protein Hrb98DE is involved in post-transcriptional control of sugar metabolism in early embryogenesis and partially validate this hypothesis using Hrb98DE knockdown. In summary, we present a systems biology framework for the identification of post-transcriptional gene regulation from large-scale, time-resolved transcriptome and proteome data.

Fluorescent Guide RNAs Facilitate Development of Layered Pol II-Driven CRISPR Circuits

Efficient clustered regularly interspaced short palindromic repeat (CRISPR) guide RNA (gRNA) expression from RNA Polymerase II (Pol II) promoters will aid in construction of complex CRISPR-based synthetic gene networks. Yet, we require tools to properly visualize gRNA directly to quantitatively study the corresponding network behavior. To address this need, we employed a fluorescent gRNA (fgRNA) to visualize synthetic CRISPR network dynamics without affecting gRNA functionality. We show that studying gRNA dynamics directly enables circuit modification and improvement of network function in Pol II-driven CRISPR circuits. This approach generates information necessary for optimizing the overall function of these networks and provides insight into the hurdles remaining in Pol II-regulated gRNA expression.

Post-Turing tissue pattern formation: Advent of mechanochemistry

Chemical and mechanical pattern formation is fundamental during embryogenesis and tissue development. Yet, the underlying molecular and cellular mechanisms are still elusive in many cases. Most current theories assume that tissue development is driven by chemical processes: either as a sequence of chemical patterns each depending on the previous one, or by patterns spontaneously arising from specific chemical interactions (such as “Turing-patterns”). Within both theories, mechanical patterns are usually regarded as passive by-products of chemical pre-patters. However, several experiments question these theories, and an increasing number of studies shows that tissue mechanics can actively influence chemical patterns during development. In this study, we thus focus on the interplay between chemical and mechanical processes during tissue development. On one hand, based on recent experimental data, we develop new mechanochemical simulation models of evolving tissues, in which the full 3D representation of the tissue appears to be critical for obtaining a realistic mechanochemical behaviour. The presented modelling approach is flexible and numerically studied using state of the art finite element methods. Thus, it may serve as a basis to combine simulations with new experimental methods in tissue development. On the other hand, we apply the developed approach and demonstrate that even simple interactions between tissue mechanics and chemistry spontaneously lead to robust and complex mechanochemical patterns. Especially, we demonstrate that the main contradictions arising in the framework of purely chemical theories are naturally and automatically resolved using the mechanochemical patterning theory.

During embryogenesis, biological tissues gradually increase their complexity by self-organised creation of diverse chemical and mechanical patterns. Detailed mechanisms driving and controlling these patterns are not well understood. Previous theories mostly assume that these patterns are driven by chemical processes. Based on these theories, mechanical patterns are usually considered being mainly determined by chemical pre-patterns. However, experimental evidence for these theories is sparse, and several inconsistencies have been discovered. Furthermore, an increasing amount of data shows that tissue mechanics plays an important role in pattern formation. In this study, we present 3D computer simulations of evolving tissues to investigate the capacity of mechanochemical interactions for pattern formation. We show that even simple interactions between tissue mechanics and tissue chemistry spontaneously lead to robust chemical and mechanical pattern formation. We additionally demonstrate that main contradictions arising in the framework of purely chemical theories are naturally and automatically resolved using the mechanochemical patterning theory. The presented modelling approach can be used to combine simulations with recent experimental developments, to help unravel one of the big mysteries in biology: The mechanisms of self-organised pattern formation during embryogenesis.

Correlation Analyses Reveal a Limited Role of Transcription in Genome-Wide Differential MicroRNA Expression in Mammals

Transcription initiates the cascade of gene expression and is often assumed to play a predominant role in determining how much gene products are ultimately expressed. The relationship between mRNA levels and protein levels has been studied extensively to reveal the degrees of transcriptional and post-transcriptional regulation of protein expression. The extent to which transcription globally controls the differential expression of non-coding RNAs, however, is poorly defined. MicroRNAs (miRNAs) are a class of small, non-coding RNAs whose biogenesis involves transcription followed by extensive processing. Here, using hundreds of datasets produced from the ENCODE (Encyclopedia of DNA Elements) project we calculated the correlations between transcriptional activity and mature miRNA expression in diverse human cells, human tissues, and mouse tissues. While correlations vary among samples, most correlation coefficients are small. Interestingly, excluding miRNAs that were discovered later or weighting miRNA expression improves the correlations. Our results suggest that transcription contributes only modestly to differential miRNA expression at the genome-wide scale in mammals.

Comparative transcriptomic and proteomic analysis of Arthrobacter sp. CGMCC 3584 responding to dissolved oxygen for cAMP production

Arthrobacter sp. CGMCC 3584 is able to produce high yields of extracellular cyclic adenosine monophosphate (cAMP), which plays a vital role in the field of treatment of disease and animal food, during aerobic fermentation. However, the molecular basis of cAMP production in Arthrobacter species is rarely explored. Here, for the first time, we report the comparative transcriptomic and proteomic study of Arthrobacter cells to elucidate the higher productivity of cAMP under high oxygen supply. We finally obtained 14.1% and 19.3% of the Arthrobacter genome genes which were up-regulated and down-regulated notably, respectively, with high oxygen supply, and identified 54 differently expressed proteins. Our results revealed that high oxygen supply had two major effects on metabolism: inhibition of glycolysis, pyruvate metabolism, nitrogen metabolism, and amino acid metabolism (histidine, branched-chain amino acids and glutamate metabolism); enhancement of the tricarboxylic acid cycle and purine metabolism. We also found that regulation of adenylate cyclase and phosphodiesterase was not significant under high oxygen supply, suggesting efficient cAMP export might be important in cAMP production. These findings may contribute to further understanding of capacities of Arthrobacter species and would be highly useful in genetic regulation for desirable production.

Quantitating translational control: mRNA abundance-dependent and independent contributions and the mRNA sequences that specify them

Translation rate per mRNA molecule correlates positively with mRNA abundance. As a result, protein levels do not scale linearly with mRNA levels, but instead scale with the abundance of mRNA raised to the power of an ‘amplification exponent’. Here we show that to quantitate translational control, the translation rate must be decomposed into two components. One, TR_mD, depends on the mRNA level and defines the amplification exponent. The other, TR_mIND, is independent of mRNA amount and impacts the correlation coefficient between protein and mRNA levels. We show that in Saccharomyces cerevisiae TR_mD represents ∼20% of the variance in translation and directs an amplification exponent of 1.20 with a 95% confidence interval [1.14, 1.26]. TR_mIND constitutes the remaining ∼80% of the variance in translation and explains ∼5% of the variance in protein expression. We also find that TR_mD and TR_mIND are preferentially determined by different mRNA sequence features: TR_mIND by the length of the open reading frame and TR_mD both by a ∼60 nucleotide element that spans the initiating AUG and by codon and amino acid frequency. Our work provides more appropriate estimates of translational control and implies that TR_mIND is under different evolutionary selective pressures than TR_mD.

Comparative proteomic analysis provides novel insights into chlorophyll biosynthesis in celery under temperature stress

Chlorophyll (Chl) is essential for light harvesting and energy transduction in photosynthesis. A proper amount of Chl within plant cells is important to celery (Apium graveolens) yield and quality. Temperature stress is an influential abiotic stress affecting Chl biosynthesis and plant growth. There are limited proteomic studies regarding Chl accumulation under temperature stress in celery leaves. Here, the proteins from celery leaves under different temperature treatments (4, 25 and 38°C) were analyzed using a proteomic approach. There were 71 proteins identified through MALDI-TOF-TOF analysis. The relative abundance of proteins involved in carbohydrate and energy metabolism, protein metabolism, amino acid metabolism, antioxidant and polyamine biosynthesis were enhanced under cold stress. These temperature stress-responsive proteins may establish a new homeostasis to enhance temperature tolerance. Magnesium chelatase (Mg-chelatase) and glutamate-1-semialdehyde aminotransferase (GSAT), related to Chl biosynthesis, showed increased abundances under cold stress. Meanwhile, the Chl contents were decreased in heat- and cold-stressed celery leaves. The inhibition of Chl biosynthesis may be due to the downregulated mRNA levels of 15 genes involved in Chl biosynthesis. The study will expand our knowledge on Chl biosynthesis and the temperature tolerance mechanisms in celery leaves.

A code for transcription elongation speed

The two major steps of gene expression are transcription and translation. While hundreds of studies regarding the effect of sequence features on the translation elongation process have been published, very few connect sequence features to the transcription elongation rate. We suggest, for the first time, that short transcript sub-sequences have a typical effect on RNA polymerase (RNAP) speed: we show that nucleotide 5-mers tend to have typical RNAP speed (or transcription rate), which is consistent along different parts of genes and among different groups of genes with high correlation. We also demonstrate that relative RNAP speed correlates with mRNA levels of endogenous and heterologous genes. Furthermore, we show that the estimated transcription and translation elongation rates correlate in endogenous genes. Finally, we demonstrate that our results are consistent for different high resolution experimental measurements of RNAP densities. These results suggest for the first time that transcription elongation is partly encoded in the transcript, affected by the codon-usage, and optimized by evolution with a significant effect on gene expression and organismal fitness.

stAIcalc: tRNA adaptation index calculator based on species-specific weights

Summary

The tRNA Adaptation Index (tAI) is a tRNA-centric measure of translation efficiency which includes weights that take into account the efficiencies of the different wobble interactions. To enable the calculation of the index based on a species-specific inference of these weights, we created the stAI calc . The calculator includes optimized tAI weights for 100 species from the three domains of life along with a standalone software package that optimizes the weights for new organisms. The tAI with the optimized weights should enable performing large scale studies in disciplines such as molecular evolution, genomics, systems biology and synthetic biology.

Availability and Implementation

The calculator is publicly available at http://www.cs.tau.ac.il/∼tamirtul/stAIcalc/stAIcalc.html.

Contact

tamirtul@post.tau.ac.il.

Analysis of Light- and Carbon-Specific Transcriptomes Implicates a Class of G-Protein-Coupled Receptors in Cellulose Sensing

In fungi, most metabolic processes are subject to regulation by light. For Trichoderma reesei, light-dependent regulation of cellulase gene expression is specifically shown. Therefore, we intended to unravel the relationship between regulation of enzymes by the carbon source and regulation of enzymes by light. Our two-dimensional analysis included inducing and repressing carbon sources which we used to compare light-specific regulation to dark-specific regulation and to rule out effects specific for a single carbon source. We found close connections with respect to gene regulation as well as significant differences in dealing with carbon in the environment in light and darkness. Moreover, our analyses showed an intricate regulation mechanism for substrate degradation potentially involving surface sensing and provide a basis for knowledge-based screening for strain improvement.

In fungi, most metabolic processes are subject to regulation by light. Trichoderma reesei is adapted to degradation of plant cell walls and regulates production of the required enzymes in a manner dependent on the nutrient source and the light status. Here we investigated the interrelated relevance of two regulation levels of the transcriptome of T. reesei: light regulation and carbon source-dependent control. We show that the carbon source (cellulose, lactose, sophorose, glucose, or glycerol) is the major source of variation, with light having a modulating effect on transcript regulation. A total of 907 genes were regulated under cellulase-inducing conditions in light, and 947 genes were regulated in darkness, with 530 genes overlapping (1,324 in total). Only 218 of the 1,324 induction-specific genes were independent of light and not regulated by the BLR1, BLR2, and ENV1 photoreceptors. Analysis of the genomic distribution of genes regulated by light upon growth on cellulose revealed considerable overlap of light-regulated clusters with induction-specific clusters and carbohydrate-active enzyme (CAZyme) clusters. Further, we found evidence for the operation of a sensing mechanism for solid cellulosic substrates, with regulation of genes such as swo1, cip1, and cip2 or of genes encoding hydrophobins which is related to the cyclic AMP (cAMP)-dependent regulatory output of ENV1. We identified class XIII G-protein-coupled receptors (GPCRs) CSG1 and CSG2 in T. reesei as putative cellulose/glucose-sensing GPCRs. Our data indicate that the cellulase regulation pathway is bipartite, comprising a section corresponding to transcriptional regulation and one corresponding to posttranscriptional regulation, with the two connected by the function of CSG1.

IMPORTANCE In fungi, most metabolic processes are subject to regulation by light. For Trichoderma reesei, light-dependent regulation of cellulase gene expression is specifically shown. Therefore, we intended to unravel the relationship between regulation of enzymes by the carbon source and regulation of enzymes by light. Our two-dimensional analysis included inducing and repressing carbon sources which we used to compare light-specific regulation to dark-specific regulation and to rule out effects specific for a single carbon source. We found close connections with respect to gene regulation as well as significant differences in dealing with carbon in the environment in light and darkness. Moreover, our analyses showed an intricate regulation mechanism for substrate degradation potentially involving surface sensing and provide a basis for knowledge-based screening for strain improvement.

Quantitative proteomics links metabolic pathways to specific developmental stages of the plant-pathogenic oomycete Phytophthora capsici

The oomycete Phytophthora capsici is a plant pathogen responsible for important losses to vegetable production worldwide. Its asexual reproduction plays an important role in the rapid propagation and spread of the disease in the field. A global proteomics study was conducted to compare two key asexual life stages of P. capsici, i.e. the mycelium and cysts, to identify stage-specific biochemical processes. A total of 1200 proteins was identified using qualitative and quantitative proteomics. The transcript abundance of some of the enriched proteins was also analysed by quantitative real-time polymerase chain reaction. Seventy-three proteins exhibited different levels of abundance between the mycelium and cysts. The proteins enriched in the mycelium are mainly associated with glycolysis, the tricarboxylic acid (or citric acid) cycle and the pentose phosphate pathway, providing the energy required for the biosynthesis of cellular building blocks and hyphal growth. In contrast, the proteins that are predominant in cysts are essentially involved in fatty acid degradation, suggesting that the early infection stage of the pathogen relies primarily on fatty acid degradation for energy production. The data provide a better understanding of P. capsici biology and suggest potential metabolic targets at the two different developmental stages for disease control.

Synonymous Codons: Choose Wisely for Expression

The genetic code, which defines the amino acid sequence of a protein, also contains information that influences the rate and efficiency of translation. Neither the mechanisms nor functions of codon-mediated regulation were well understood. The prevailing model was that the slow translation of codons decoded by rare tRNAs reduces efficiency. Recent genome-wide analyses have clarified several issues. Specific codons and codon combinations modulate ribosome speed and facilitate protein folding. However, tRNA availability is not the sole determinant of rate; rather, interactions between adjacent codons and wobble base pairing are key. One mechanism linking translation efficiency and codon use is that slower decoding is coupled to reduced mRNA stability. Changes in tRNA supply mediate biological regulationfor instance,, changes in tRNA amounts facilitate cancer metastasis.

Rapid Sampling of Escherichia coli After Changing Oxygen Conditions Reveals Transcriptional Dynamics

Escherichia coli is able to shift between anaerobic and aerobic metabolism by adapting its gene expression, e.g., of metabolic genes, to the new environment. The dynamics of gene expression that result from environmental shifts are limited, amongst others, by the time needed for regulation and transcription elongation. In this study, we examined gene expression dynamics after an anaerobic-to-aerobic shift on a short time scale (0.5, 1, 2, 5, and 10 min) by RNA sequencing with emphasis on delay times and transcriptional elongation rates (TER). Transient expression patterns and timing of differential expression, characterized by delay and elongation, were identified as key features of the dataset. Gene ontology enrichment analysis revealed early upregulation of respiratory and iron-related gene sets. We inferred specific TERs of 89 operons with a mean TER of 42.0 nt/s and mean delay time of 22.4 s. TERs correlate with sequence features, such as codon bias, whereas delay times correlate with the involvement of regulators. The presented data illustrate that at very short times after a shift in oxygenation, extensional changes of the transcriptome, such as temporary responses, can be observed. Besides regulation, TERs contribute to the dynamics of gene expression.

On the Dependency of Cellular Protein Levels on mRNA Abundance

The question of how genomic information is expressed to determine phenotypes is of central importance for basic and translational life science research and has been studied by transcriptomic and proteomic profiling. Here, we review the relationship between protein and mRNA levels under various scenarios, such as steady state, long-term state changes, and short-term adaptation, demonstrating the complexity of gene expression regulation, especially during dynamic transitions. The spatial and temporal variations of mRNAs, as well as the local availability of resources for protein biosynthesis, strongly influence the relationship between protein levels and their coding transcripts. We further discuss the buffering of mRNA fluctuations at the level of protein concentrations. We conclude that transcript levels by themselves are not sufficient to predict protein levels in many scenarios and to thus explain genotype-phenotype relationships and that high-quality data quantifying different levels of gene expression are indispensable for the complete understanding of biological processes.

Advances in analyzing RNA diversity in eukaryotic transcriptomes: peering through the Omics lens

Alternative splicing, polyadenylation, and chemical modifications of RNA generate astonishing complexity within eukaryotic transcriptomes. The last decade has brought numerous advances in sequencing technologies that allow biologists to investigate these phenomena with greater depth and accuracy while reducing time and cost. A commensurate development in biochemical techniques for the enrichment and analysis of different RNA variants has accompanied the advancement of global sequencing analysis platforms. Here, we present a detailed overview of the latest biochemical methods, along with bioinformatics pipelines that have aided in identifying different RNA variants. We also highlight the ongoing developments and challenges associated with RNA variant detection and quantification, including sample heterogeneity and isolation, as well as 'Omics' big data handling.

Content of testis-specific isoform of Na/K-ATPase (ATP1A4) is increased during bovine sperm capacitation through translation in mitochondrial ribosomes

Capacitation comprises a series of structural and functional modifications of sperm that confer fertilizing ability. We previously reported that the testis-specific isoform of Na/K-ATPase (ATP1A4) regulated bovine sperm capacitation through signaling mechanisms involving kinases. During subsequent investigations to elucidate mechanisms by which ATP1A4 regulates sperm capacitation, we observed that ATP1A4 was localised in both raft and non-raft fractions of the sperm plasma membrane and that its total content was increased in both membrane fractions during capacitation. The objective of the present study was to investigate mechanism(s) of capacitation-associated increase in the content of ATP1A4. Despite the widely accepted dogma of transcriptional/translational quiescence, incubation of sperm with either ouabain (specific ligand for ATP1A4) or heparin increased ATP1A4 content in raft and non-raft sperm membrane fractions, total sperm protein extracts (immunoblotting) and fixed sperm (flow cytometry), with a concurrent increase in Na/K-ATPase enzyme activity. This capacitation-associated increase in ATP1A4 content was partially decreased by chloramphenicol (mitochondrial translation inhibitor) but not affected by actinomycin D (transcription inhibitor). To demonstrate de novo ATP1A4 synthesis, we evaluated incorporation of bodipy conjugated lysine in this protein during capacitation. A partial decrease in bodipy-lysine incorporation occurred in ATP1A4 from sperm capacitated in the presence of chloramphenicol. Therefore, increased ATP1A4 content during capacitation was attributed to mitochondrial translation of ATP1A4 mRNA present in ejaculated sperm, rather than gene transcription. To our knowledge, this is the first report demonstrating ATP1A4 synthesis during bovine sperm capacitation.

Predictive biophysical modeling and understanding of the dynamics of mRNA translation and its evolution

mRNA translation is the fundamental process of decoding the information encoded in mRNA molecules by the ribosome for the synthesis of proteins. The centrality of this process in various biomedical disciplines such as cell biology, evolution and biotechnology, encouraged the development of dozens of mathematical and computational models of translation in recent years. These models aimed at capturing various biophysical aspects of the process. The objective of this review is to survey these models, focusing on those based and/or validated on real large-scale genomic data. We consider aspects such as the complexity of the models, the biophysical aspects they regard and the predictions they may provide. Furthermore, we survey the central systems biology discoveries reported on their basis. This review demonstrates the fundamental advantages of employing computational biophysical translation models in general, and discusses the relative advantages of the different approaches and the challenges in the field.

Identifying Aspects of the Post-Transcriptional Program Governing the Proteome of the Green Alga Micromonas pusilla

Micromonas is a unicellular motile alga within the Prasinophyceae, a green algal group that is related to land plants. This picoeukaryote (<2 μm diameter) is widespread in the marine environment but is not well understood at the cellular level. Here, we examine shifts in mRNA and protein expression over the course of the day-night cycle using triplicated mid-exponential, nutrient replete cultures of Micromonas pusilla CCMP1545. Samples were collected at key transition points during the diel cycle for evaluation using high-throughput LC-MS proteomics. In conjunction, matched mRNA samples from the same time points were sequenced using pair-ended directional Illumina RNA-Seq to investigate the dynamics and relationship between the mRNA and protein expression programs of M. pusilla. Similar to a prior study of the marine cyanobacterium Prochlorococcus, we found significant divergence in the mRNA and proteomics expression dynamics in response to the light:dark cycle. Additionally, expressional responses of genes and the proteins they encoded could also be variable within the same metabolic pathway, such as we observed in the oxygenic photosynthesis pathway. A regression framework was used to predict protein levels from both mRNA expression and gene-specific sequence-based features. Several features in the genome sequence were found to influence protein abundance including codon usage as well as 3’ UTR length and structure. Collectively, our studies provide insights into the regulation of the proteome over a diel cycle as well as the relationships between transcriptional and translational programs in the widespread marine green alga Micromonas.

Pervasive isoform-specific translational regulation via alternative transcription start sites in mammals

Transcription initiated at alternative sites can produce mRNA isoforms with different 5'UTRs, which are potentially subjected to differential translational regulation. However, the prevalence of such isoform-specific translational control across mammalian genomes is currently unknown. By combining polysome profiling with high-throughput mRNA 5' end sequencing, we directly measured the translational status of mRNA isoforms with distinct start sites. Among 9,951 genes expressed in mouse fibroblasts, we identified 4,153 showed significant initiation at multiple sites, of which 745 genes exhibited significant isoform-divergent translation. Systematic analyses of the isoform-specific translation revealed that isoforms with longer 5'UTRs tended to translate less efficiently. Further investigation of cis-elements within 5'UTRs not only provided novel insights into the regulation by known sequence features, but also led to the discovery of novel regulatory sequence motifs. Quantitative models integrating all these features explained over half of the variance in the observed isoform-divergent translation. Overall, our study demonstrated the extensive translational regulation by usage of alternative transcription start sites and offered comprehensive understanding of translational regulation by diverse sequence features embedded in 5'UTRs.

The ribosome in action: Tuning of translational efficiency and protein folding

The cellular proteome is shaped by the combined activities of the gene expression and quality control machineries. While transcription plays an undoubtedly important role, in recent years also translation emerged as a key step that defines the composition and quality of the proteome and the functional activity of proteins in the cell. Among the different post-transcriptional control mechanisms, translation initiation and elongation provide multiple checkpoints that can affect translational efficiency. A multitude of specific signals in mRNAs can determine the frequency of translation initiation, choice of the open reading frame, global and local elongation velocities, and the folding of the emerging protein. In addition to specific signatures in the mRNAs, also variations in the global pools of translation components, including ribosomes, tRNAs, mRNAs, and translation factors can alter translational efficiencies. The cellular outcomes of phenomena such as mRNA codon bias are sometimes difficult to understand due to the staggering complexity of covariates that affect codon usage, translation, and protein folding. Here we summarize the experimental evidence on how the ribosome-together with the other components of the translational machinery-can alter translational efficiencies of mRNA at the initiation and elongation stages and how translation velocity affects protein folding. We seek to explain these findings in the context of mechanistic work on the ribosome. The results argue in favour of a new understanding of translation control as a hub that links mRNA homeostasis to production and quality control of proteins in the cell.

Decoding Cellular Dynamics in Epidermal Growth Factor Signaling Using a New Pathway-Based Integration Approach for Proteomics and Transcriptomics Data

Identification of dynamic signaling mechanisms on different cellular layers is now facilitated as the increased usage of various high-throughput techniques goes along with decreasing costs for individual experiments. A lot of these signaling mechanisms are known to be coordinated by their dynamics, turning time-course data sets into valuable information sources for inference of regulatory mechanisms. However, the combined analysis of parallel time-course measurements from different high-throughput platforms still constitutes a major challenge requiring sophisticated bioinformatic tools in order to ease biological interpretation. We developed a new pathway-based integration approach for the analysis of coupled omics time-series data, which we implemented in the R package pwOmics. Unlike many other approaches, our approach acknowledges the role of the different cellular layers of measurement and infers consensus profiles and time profile clusters for further biological interpretation. We investigated a time-course data set on epidermal growth factor stimulation of human mammary epithelial cells generated on the two layers of RNA and proteins. The data was analyzed using our new approach with a focus on feedback signaling and pathway crosstalk. We could confirm known regulatory patterns relevant in the physiological cellular response to epidermal growth factor stimulation as well as identify interesting new interactions in this signaling context, such as the regulatory influence of the connective tissue growth factor on transferrin receptor or the influence of growth arrest and DNA-damage-inducible alpha on the connective tissue growth factor. Thus, we show that integrated cross-platform analysis provides a deeper understanding of regulatory signaling mechanisms. Combined with time-course information it enables the characterization of dynamic signaling processes and leads to the identification of important regulatory interactions which might be dysregulated in disease with adverse effects.

Testing and Validation of Computational Methods for Mass Spectrometry

High-throughput methods based on mass spectrometry (proteomics, metabolomics, lipidomics, etc.) produce a wealth of data that cannot be analyzed without computational methods. The impact of the choice of method on the overall result of a biological study is often underappreciated, but different methods can result in very different biological findings. It is thus essential to evaluate and compare the correctness and relative performance of computational methods. The volume of the data as well as the complexity of the algorithms render unbiased comparisons challenging. This paper discusses some problems and challenges in testing and validation of computational methods. We discuss the different types of data (simulated and experimental validation data) as well as different metrics to compare methods. We also introduce a new public repository for mass spectrometric reference data sets ( http://compms.org/RefData ) that contains a collection of publicly available data sets for performance evaluation for a wide range of different methods.

Differential Analysis of the Secretome of WRL68 Cells Infected with the Chikungunya Virus

The Chikungunya virus (CHIKV) is an arthropod borne virus. In the last 50 years, it has been the cause of numerous outbreaks in tropical and temperate regions, worldwide. There is limited understanding regarding the underlying molecular mechanisms involved in CHIKV replication and how the virus interacts with its host. In the present study, comparative proteomics was used to identify secreted host proteins that changed in abundance in response to early CHIKV infection. Two-dimensional gel electrophoresis was used to analyse and compare the secretome profiles of WRL-68 cells infected with CHIKV against mock control WRL-68 cells. The analysis identified 25 regulated proteins in CHIKV infected cells. STRING network analysis was then used to predict biological processes that may be affected by these proteins. The processes predicted to be affected include signal transduction, cellular component and extracellular matrix (ECM) organization, regulation of cytokine stimulus and immune response. These results provide an initial view of CHIKV may affect the secretome of infected cells during early infection. The results presented here will compliment earlier results from the study of late host response. However, functional characterization will be necessary to further enhance our understanding of the roles played by these proteins in the early stages of CHIKV infection in humans.

Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast

Cells respond to their environment by modulating protein levels through mRNA transcription and post-transcriptional control. Modest observed correlations between global steady-state mRNA and protein measurements have been interpreted as evidence that mRNA levels determine roughly 40% of the variation in protein levels, indicating dominant post-transcriptional effects. However, the techniques underlying these conclusions, such as correlation and regression, yield biased results when data are noisy, missing systematically, and collinear---properties of mRNA and protein measurements---which motivated us to revisit this subject. Noise-robust analyses of 24 studies of budding yeast reveal that mRNA levels explain more than 85% of the variation in steady-state protein levels. Protein levels are not proportional to mRNA levels, but rise much more rapidly. Regulation of translation suffices to explain this nonlinear effect, revealing post-transcriptional amplification of, rather than competition with, transcriptional signals. These results substantially revise widely credited models of protein-level regulation, and introduce multiple noise-aware approaches essential for proper analysis of many biological phenomena.

Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast

Cells respond to their environment by modulating protein levels through mRNA transcription and post-transcriptional control. Modest observed correlations between global steady-state mRNA and protein measurements have been interpreted as evidence that mRNA levels determine roughly 40% of the variation in protein levels, indicating dominant post-transcriptional effects. However, the techniques underlying these conclusions, such as correlation and regression, yield biased results when data are noisy, missing systematically, and collinear---properties of mRNA and protein measurements---which motivated us to revisit this subject. Noise-robust analyses of 24 studies of budding yeast reveal that mRNA levels explain more than 85% of the variation in steady-state protein levels. Protein levels are not proportional to mRNA levels, but rise much more rapidly. Regulation of translation suffices to explain this nonlinear effect, revealing post-transcriptional amplification of, rather than competition with, transcriptional signals. These results substantially revise widely credited models of protein-level regulation, and introduce multiple noise-aware approaches essential for proper analysis of many biological phenomena.

Integrating -Omics: Systems Biology as Explored Through C. elegans Research

-Omics data have become indispensable to systems biology, which aims to describe the full complexity of functional cells, tissues, organs and organisms. Generating vast amounts of data via such methods, researchers have invested in ways of handling and interpreting these. From the large volumes of -omics data that have been gathered over the years, it is clear that the information derived from one -ome is usually far from complete. Now, individual techniques and methods for integration are maturing to the point that researchers can focus on network-based integration rather than simply interpreting single -ome studies. This review evaluates the application of integrated -omics approaches with a focus on Caenorhabditis elegans studies, intending to direct researchers in this field to useful databases and inspiring examples.

Kinome profiling reveals breast cancer heterogeneity and identifies targeted therapeutic opportunities for triple negative breast cancer

Our understanding of breast cancer heterogeneity at the protein level is limited despite proteins being the ultimate effectors of cellular functions. We investigated the heterogeneity of breast cancer (41 primary tumors and 15 breast cancer cell lines) at the protein and phosphoprotein levels to identify activated oncogenic pathways and developing targeted therapeutic strategies. Heterogeneity was observed not only across histological subtypes, but also within subtypes. Tumors of the Triple negative breast cancer (TNBC) subtype distributed across four different clusters where one cluster (cluster ii) showed high deregulation of many proteins and phosphoproteins. The majority of TNBC cell lines, particularly mesenchymal lines, resembled the cluster ii TNBC tumors. Indeed, TNBC cell lines were more sensitive than non-TNBC cell lines when treated with targeted inhibitors selected based on upregulated pathways in cluster ii. In line with the enrichment of the upregulated pathways with onco-clients of Hsp90, we found synergy in combining Hsp90 inhibitors with several kinase inhibitors, particularly Erk5 inhibitors. The combination of Erk5 and Hsp90 inhibitors was effective in vitro and in vivo against TNBC leading to upregulation of pro-apoptotic effectors. Our studies contribute to proteomic profiling and improve our understanding of TNBC heterogeneity to provide therapeutic opportunities for this disease.

Expression of (pro)renin receptor and its upregulation by high salt intake in the rat nephron

A functional receptor for renin and prorenin ((P)RR) was identified as a new component of the renin-angiotensin system. The precise localization of (P)RR in the kidney has not been clarified. The present study was designed to determine the localization of (P)RR in the rat nephron and to investigate the regulation of renal (P)RR expression by high salt (HS) intake. (P)RR mRNA levels in the kidney sections and isolated nephron segments were examined using reverse transcription and polymerase chain reaction (RT-PCR), and (P)RR protein levels were examined by immunoblot and immunohistochemical analyses. Renal (P)RR mRNA and protein levels in rats fed a HS diet for 4 weeks were also compared with those fed a normal salt diet. (P)RR mRNA was expressed in various nephron segments of the cortex and medulla; glomeruli (Glm), proximal tubules (PT), thick ascending limbs (TAL) and collecting ducts (CD). (P)RR protein was highly expressed in the PT, medullary TAL (MTAL) and inner medullary CD (IMCD), and lowly in the preglomerular arterioles (Art) and Glm. HS intake increased (P)RR protein levels in the Glm, PT and tubules of medullary rays. These results indicated that (P)RR is expressed throughout various nephron segments and Art, and that (P)RR protein is expressed predominantly in the PT, MTAL and IMCD. HS intake appears to upregulate the (P)RR expression in the Glm, PT and tubules of medullary rays, suggesting that (P)RR may be involved in the regulation of renal function and HS-induced disorders.