While classical breeding traits have focussed on above‐ground tissues, it is becoming clear that underground aspects of plant life are a hidden treasure of tools applicable for resilient crop production. Plants of the legume family develop specialized organs, called nodules, which serve as hosts for Rhizobium bacteroids. A highly specialized symbiotic relationship exists deep inside the nodules. In

Biological nitrogen fixation emerging from the symbiosis between bacteria and crop plants holds promise to increase the sustainability of agriculture. One of the biggest hurdles for the engineering of nitrogen‐fixing organisms is an incomplete knowledge of metabolic interactions between microbe and plant. In contrast to the previously assumed supply of only succinate, we describe here the CATCH ‐N

Neurodegenerative diseases are a growing burden, and there is an urgent need for better biomarkers for diagnosis, prognosis, and treatment efficacy. Structural and functional brain alterations are reflected in the protein composition of cerebrospinal fluid (CSF ). Alzheimer's disease (AD ) patients have higher CSF levels of tau, but we lack knowledge of systems‐wide changes of CSF protein levels that

Rational molecular engineering of proteins with CRISPR ‐based approaches is challenged by the gene‐centric nature of gRNA design tools. To address this, we have developed CRISPR ‐TAPE , a protein‐centric gRNA design algorithm that allows users to target specific residues, or amino acid types within proteins. gRNA outputs can be customized to support maximal efficacy of homology‐directed repair for

Mathematical models can enable a predictive understanding of mechanism in cell biology by quantitatively describing complex networks of interactions, but such models are often poorly constrained by available data. Owing to its relative biochemical simplicity, the core circadian oscillator in Synechococcus elongatus has become a prototypical system for studying how collective dynamics emerge from molecular

Microscopy is a powerful tool for characterizing complex cellular phenotypes, but linking these phenotypes to genotype or RNA expression at scale remains challenging. Here, we present Visual Cell Sorting, a method that physically separates hundreds of thousands of live cells based on their visual phenotype. Automated imaging and phenotypic analysis directs selective illumination of Dendra2, a photoconvertible

Fitness of bacteria is determined both by how fast cells grow when nutrients are abundant and by how well they survive when conditions worsen. Here, we study how prior growth conditions affect the death rate of Escherichia coli during carbon starvation. We control the growth rate prior to starvation either via the carbon source or via a carbon‐limited chemostat. We find a consistent dependence where

The formation of spatiotemporal patterns of gene expression is frequently guided by gradients of diffusible signaling molecules. The toggle switch subnetwork, composed of two cross‐repressing transcription factors, is a common component of gene regulatory networks in charge of patterning, converting the continuous information provided by the gradient into discrete abutting stripes of gene expression

Pooled genetic screening is a powerful method to systematically link genotype to phenotype and gain insights into biological processes, but applying it to visual phenotypes such as cell morphology or protein localization has remained a challenge. In their recent work, Fowler and colleagues (Hasle et al , 2020) describe an elegant approach for high‐throughput cell sorting according to visual phenotypes

A progressive loss of protein homeostasis is characteristic of aging and a driver of neurodegeneration. To investigate this process quantitatively, we characterized proteome dynamics during brain aging in the short‐lived vertebrate Nothobranchius furzeri combining transcriptomics and proteomics. We detected a progressive reduction in the correlation between protein and mRNA , mainly due to post‐transcriptional

Automated cell type identification is a key computational challenge in single‐cell RNA ‐sequencing (scRNA ‐seq) data. To capitalise on the large collection of well‐annotated scRNA ‐seq datasets, we developed scClassify, a multiscale classification framework based on ensemble learning and cell type hierarchies constructed from single or multiple annotated datasets as references. scClassify enables the

Comprehensive molecular‐level models of human metabolism have been generated on a cellular level. However, models of whole‐body metabolism have not been established as they require new methodological approaches to integrate molecular and physiological data. We developed a new metabolic network reconstruction approach that used organ‐specific information from literature and omics data to generate two

Cell growth and quiescence in eukaryotic cells is controlled by an evolutionarily conserved network of signaling pathways. Signal transduction networks operate to modulate a wide range of cellular processes and physiological properties when cells exit proliferative growth and initiate a quiescent state. How signaling networks function to respond to diverse signals that result in cell cycle exit and

The C-terminal sequence of a protein is involved in processes such as efficiency of translation termination and protein degradation. However, the general relationship between features of this C-terminal sequence and levels of protein expression remains unknown. Here, we identified C-terminal amino acid biases that are ubiquitous across the bacterial taxonomy (1,582 genomes). We showed that the frequency

Single-cell technologies allow measuring chromatin accessibility and gene expression in each cell, but jointly utilizing both layers to map bona fide gene regulatory networks and enhancers remains challenging. Here, we generate independent single-cell RNA-seq and single-cell ATAC-seq atlases of the Drosophila eye-antennal disc and spatially integrate the data into a virtual latent space that mimics

Studying the spatiotemporal control of gene regulatory networks at the single-cell level is still a challenge, yet it is key to understanding the mechanisms driving cellular identity. In their recent study, Aerts and colleagues (González-Blas et al, 2020) develop a new strategy to spatially map and integrate single-cell transcriptome and epigenome profiles in the Drosophila eye-antennal disc and to

Recent studies have revealed that global extrinsic noise arising from stochasticity in the intracellular biochemical environment plays a critical role in heterogeneous cell physiologies. However, it remains largely unclear how such extrinsic noise dynamically influences downstream reactions and whether it could be neutralized by cellular reactions. Here, using fluorescent protein (FP) maturation as

Liver injury triggers adaptive remodeling of the hepatic transcriptome for repair/regeneration. We demonstrate that this involves particularly profound transcriptomic alterations where acute induction of genes involved in handling of endoplasmic reticulum stress (ERS) is accompanied by partial hepatic dedifferentiation. Importantly, widespread hepatic gene downregulation could not simply be ascribed

Streptavidin-mediated enrichment is a powerful strategy to identify biotinylated biomolecules and their interaction partners; however, intense streptavidin-derived peptides impede protein identification by mass spectrometry. Here, we present an approach to chemically modify streptavidin, thus rendering it resistant to proteolysis by trypsin and LysC. This modification results in over 100-fold reduction

Endocytosis is a fundamental cellular trafficking pathway, which requires an organized assembly of the multiprotein endocytic coat to pull the plasma membrane into the cell. Although the protein composition of the endocytic coat is known, its functional architecture is not well understood. Here, we determine the nanoscale organization of the endocytic coat by FRET microscopy in yeast Saccharomyces

The prevalence of non-alcoholic fatty liver disease (NAFLD) continues to increase dramatically, and there is no approved medication for its treatment. Recently, we predicted the underlying molecular mechanisms involved in the progression of NAFLD using network analysis and identified metabolic cofactors that might be beneficial as supplements to decrease human liver fat. Here, we first assessed the

Prostate cancer (PCa) has a broad spectrum of clinical behavior; hence, biomarkers are urgently needed for risk stratification. Here, we aim to find potential biomarkers for risk stratification, by utilizing a gene co-expression network of transcriptomics data in addition to laser-microdissected proteomics from human and murine prostate FFPE samples. We show up-regulation of oxidative phosphorylation

Cells balance glycolysis with respiration to support their metabolic needs in different environmental or physiological contexts. With abundant glucose, many cells prefer to grow by aerobic glycolysis or fermentation. Using 161 natural isolates of fission yeast, we investigated the genetic basis and phenotypic effects of the fermentation-respiration balance. The laboratory and a few other strains depended

Alternative polyadenylation (APA) is a major layer of gene regulation. However, it has recently been argued that most APA represents molecular noise. To clarify their functional relevance and evolution, we quantified allele-specific APA patterns in multiple tissues from an F1 hybrid mouse. We found a clearly negative correlation between gene expression and APA diversity for the 2,866 genes (24.9%)

Transcription factors (TFs) control the rate of mRNA production. Technological advances have made the task of measuring mRNA levels for all genes straightforward, but identifying causal relationships between TFs and their target genes remains an unsolved problem in biology. In their recent study, McIsaac and colleagues (Hackett et al, 2020) apply a method for inducing the overexpression of a TF and

Cellular DNA barcoding has become a popular approach to study heterogeneity of cell populations and to identify clones with differential response to cellular stimuli. However, there is a lack of reliable methods for statistical inference of differentially responding clones. Here, we used mixtures of DNA-barcoded cell pools to generate a realistic benchmark read count dataset for modelling a range of

We present IDEA (the Induction Dynamics gene Expression Atlas), a dataset constructed by independently inducing hundreds of transcription factors (TFs) and measuring timecourses of the resulting gene expression responses in budding yeast. Each experiment captures a regulatory cascade connecting a single induced regulator to the genes it causally regulates. We discuss the regulatory cascade of a single

Profiling of biological relationships between different molecular layers dissects regulatory mechanisms that ultimately determine cellular function. To thoroughly assess the role of protein post-translational turnover, we devised a strategy combining pulse stable isotope-labeled amino acids in cells (pSILAC), data-independent acquisition mass spectrometry (DIA-MS), and a novel data analysis framework

Deep mutational scanning can provide significant insights into the function of essential genes in bacteria. Here, we developed a high-throughput method for mutating essential genes of Escherichia coli in their native genetic context. We used Cas9-mediated recombineering to introduce a library of mutations, created by error-prone PCR, within a gene fragment on the genome using a single gRNA pre-validated

Different tissues express genes with particular codon usage and anticodon tRNA repertoires. However, the codon-anticodon co-adaptation in humans is not completely understood, nor is its effect on tissue-specific protein levels. Here, we first validated the accuracy of small RNA-seq for tRNA quantification across five human cell lines. We then analyzed the tRNA abundance of more than 8,000 tumor samples

Characterising context-dependent gene functions is crucial for understanding the genetic bases of health and disease. To date, inference of gene functions from large-scale genetic perturbation screens is based on ad hoc analysis pipelines involving unsupervised clustering and functional enrichment. We present Knowledge- and Context-driven Machine Learning (KCML), a framework that systematically predicts

Thermal proteome profiling (TPP) is based on the principle that, when subjected to heat, proteins denature and become insoluble. Proteins can change their thermal stability upon interactions with small molecules (such as drugs or metabolites), nucleic acids or other proteins, or upon post-translational modifications. TPP uses multiplexed quantitative mass spectrometry-based proteomics to monitor the

Synthetic genetic circuits offer the potential to wield computational control over biology, but their complexity is limited by the accuracy of mathematical models. Here, we present advances that enable the complete encoding of an electronic chip in the DNA carried by Escherichia coli (E. coli). The chip is a binary-coded digit (BCD) to 7-segment decoder, associated with clocks and calculators, to turn

How cells utilize surface receptors for chemoreception is a recurrent question spanning between physics and biology over the past few decades. However, the dynamical mechanism for processing time-varying signals is still unclear. Using dynamical systems formalism to describe criticality in non-equilibrium systems, we propose generic principle for temporal information processing through phase space

The mechanisms of organ size control remain poorly understood. A key question is how cells collectively sense the overall status of a tissue. We addressed this problem focusing on mouse liver regeneration. Using digital tissue reconstruction and quantitative image analysis, we found that the apical surface of hepatocytes forming the bile canalicular network expands concomitant with an increase in F-actin

Mechanistic modeling of signaling pathways mediating patient-specific response to therapy can help to unveil resistance mechanisms and improve therapeutic strategies. Yet, creating such models for patients, in particular for solid malignancies, is challenging. A major hurdle to build these models is the limited material available that precludes the generation of large-scale perturbation data. Here

Our ability to understand the genotype-to-phenotype relationship is hindered by the lack of detailed understanding of phenotypes at a single-cell level. To systematically assess cell-to-cell phenotypic variability, we combined automated yeast genetics, high-content screening and neural network-based image analysis of single cells, focussing on genes that influence the architecture of four subcellular

Gene expression variability in mammalian systems plays an important role in physiological and pathophysiological conditions. This variability can come from differential regulation related to cell state (extrinsic) and allele-specific transcriptional bursting (intrinsic). Yet, the relative contribution of these two distinct sources is unknown. Here, we exploit the qualitative difference in the patterns

High-throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples from a variety of sources, including fresh-frozen tissue, FFPE tissue, or blood. To reach this goal, we have implemented single-pot solid-phase-enhanced sample preparation (SP3) on a liquid handling robot for automated processing (autoSP3) of tissue lysates in a 96-well format. AutoSP3

Dynamic mechanistic models, that is, those that can simulate behavior over time courses, are a cornerstone of molecular systems biology. They are being used to model molecular mechanisms with varying degrees of granularity-from elementary reactions to causal links-and to describe these systems by various dynamic mathematical frameworks, such as Boolean networks or systems of differential equations

Arrayed CRISPR-based screens emerge as a powerful alternative to pooled screens making it possible to investigate a wide range of cellular phenotypes that are typically not amenable to pooled screens. Here, we describe a solid-phase transfection platform that enables CRISPR-based genetic screens in arrayed format with flexible readouts. We demonstrate efficient gene knockout upon delivery of guide

While prokaryotic promoters controlled by signal-responding regulators typically display a range of input/output ratios when exposed to cognate inducers, virtually no naturally occurring cases are known to have an OFF state of zero transcription-as ideally needed for synthetic circuits. To overcome this problem, we have modelled and implemented a simple digitalizer module that completely suppresses

Recent developments in proteomics have enabled signaling studies where > 10,000 phosphosites can be routinely identified and quantified. Yet, current analyses are limited in throughput, reproducibility, and robustness, hampering experiments that involve multiple perturbations, such as those needed to map kinase-substrate relationships, capture pathway crosstalks, and network inference analysis. To

Metabolic heterogeneity between individual cells of a population harbors significant challenges for fundamental and applied research. Identifying metabolic heterogeneity and investigating its emergence require tools to zoom into metabolism of individual cells. While methods exist to measure metabolite levels in single cells, we lack capability to measure metabolic flux, i.e., the ultimate functional

Loss-of-function (LoF) mutations associated with disease do not manifest equally in different individuals. The impact of the genetic background on the consequences of LoF mutations remains poorly characterized. Here, we systematically assessed the changes in gene deletion phenotypes for 3,786 gene knockouts in four Saccharomyces cerevisiae strains and 38 conditions. We observed 18.5% of deletion phenotypes

During embryogenesis, differentiation of pluripotent cells into somatic cell types depends both on signaling cues and intrinsic gene expression programs. While the molecular underpinnings of pluripotency are well mapped, much less is known on how mouse embryonic stem cells (mESCs) differentiate. Using RNA-Seq profiling during specification to the three germ layers, we showed that mESCs switched on

Molecular Systems Biology warmly welcomes its new academic Chief Editor, M. Madan Babu. Madan shared his thoughts on the evolution of the field and the importance of bridging disciplines to enable next generation systems biology.

Biology is reaching a convergence point of its historic reductionist and modern holistic approaches to understanding the living system. Structural biology has historically taken the reductionist approach to deeply probe the inner workings of complex molecular machines. In contrast, systems biology and genome-scale modeling have organically grown out of the wealth of data now being generated by diverse

Multiple sequence alignments are fundamental to many sequence analysis methods. Most alignments are computed using the progressive alignment heuristic. These methods are starting to become a bottleneck in some analysis pipelines when faced with data sets of the size of many thousands of sequences. Some methods allow computation of larger data sets while sacrificing quality, and others produce high‐quality

We have systematically made a set of precisely defined, single‐gene deletions of all nonessential genes in Escherichia coli K‐12. Open‐reading frame coding regions were replaced with a kanamycin cassette flanked by FLP recognition target sites by using a one‐step method for inactivation of chromosomal genes and primers designed to create in‐frame deletions upon excision of the resistance cassette.

The log-rank test statistic is very broadly used in biology. Unfortunately, P-values based on the popular chi-square approximation are often inaccurate and can be misleading.