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Tapetum development and pollen production are regulated by a complex transcriptional network that consists of a group of tapetum-specific Arabidopsis transcription factors (TFs). Among these TFs, DEFECTIVE IN TAPETAL DEVELOPMENT AND FUNCTION 1 (TDF1) encodes an R2R3 MYB factor, and ABORTED MICROSPORE (AMS) encodes a basic helix-loop-helix (bHLH) factor. However, knowledge regarding the regulatory role of TDF1 in anther development remains limited. Here, we discovered that TDF1 directly regulates AMS via an AACCT cis-element. We found the precocious AMS transcript and absence of AMS protein in ams _/_ gpTDF1:AMS-FLAG lines, suggesting the timing of the TDF1-regulated AMS expression is a prerequisite for AMS functioning. We found that TDF1 interacts with AMS. Additionally, the TDF1–AMS complex additively promotes the expression of AMS-regulated genes, suggesting that TDF1 and AMS regulate the downstream genes through a feed-forward loop. EPXB5, encoding a beta-expansin family protein, is another direct target of TDF1, and it is highly expressed in the tapetum and pollen grains. The TDF1–AMS complex acts in concert to activate EXPB5 expression through a feed-forward loop. The identification of the regulatory pathway between TDF1 and AMS provides an interlocked feed-forward loop circuit that precisely regulates the transcriptional cascades that support anther development.

Linker histone H1.2 (H1.2), encoded by HIST1H1C (H1C), is a major H1 variant in somatic cells. Among five histone H1 somatic variants, upregulated H1.2 was found in human hepatocellular carcinoma (HCC) samples and in a diethylnitrosamine (DEN)‐induced HCC mouse model. In vitro, H1.2 overexpression accelerated proliferation of HCC cell lines, whereas H1.2 knockdown (KD) had the opposite effect. In vivo, H1.2 insufficiency or deficiency (H1c KD or H1c KO) alleviated inflammatory response and HCC development in DEN‐treated mice. Mechanistically, H1.2 regulated the activation of signal transducer and activator of transcription 3 (STAT3), which in turn positively regulated H1.2 expression by binding to its promoter. Moreover, upregulation of the H1.2/STAT3 axis was observed in human HCC samples, and was confirmed in mouse models of methionine‐choline‐deficient diet induced nonalcoholic steatohepatitis or lipopolysaccharide induced acute inflammatory liver injury. Disrupting this feed‐forward loop by KD of STAT3 or treatment with STAT3 inhibitors rescued H1.2 overexpression‐induced proliferation. Moreover, STAT3 inhibitor treatment‐ameliorated H1.2 overexpression promoted xenograft tumor growth. Therefore, H1.2 plays a novel role in inflammatory response by regulating STAT3 activation in HCC, thus, blockade of the H1.2/STAT3 loop is a potential strategy against HCC. This study showed that histone H1.2 was upregulated in hepatocellular carcinoma samples and promoted hepatocarcinogenesis by regulating signal transducer and activator of transcription 3 (STAT3) activation. STAT3 in turn upregulated H1.2 by binding to its promoter to form a feed‐forward H1.2/STAT3 loop. The H1.2/STAT3 loop was further identified in inflammatory liver injury models.

Breast cancer is the most frequent cancer among women, and metastases in distant organs are the leading cause of the cancer‐related deaths. While survival of early‐stage breast cancer patients has increased dramatically, the 5‐year survival rate of metastatic patients has barely improved in the last 20 years. Metastases can arise up to decades after primary tumor resection, hinting at microenvironmental factors influencing the sudden outgrowth of disseminated tumor cells (DTCs). This review summarizes how the environment of the most common metastatic sites (lung, liver, bone, brain) is influenced by the primary tumor and by the varying dormancy of DTCs, with a special focus on how established metastases persist and grow in distant organs due to feed‐forward loops (FFLs). We discuss in detail the importance of FFL of cancer cells with their microenvironment including the secretome, interaction with specialized tissue‐specific cells, nutrients/metabolites, and that novel therapies should target not only the cancer cells but also the tumor microenvironment, which are thick as thieves. Graphical Abstract Metastases can arise decades after primary breast tumor resection. This review by M. Bentires‐Alj and colleagues describes how the environment of the most common metastatic sites is influenced by the primary tumor and the varying dormancy of disseminated tumor cells, with a focus on feed‐forward loops.

Hypertrophic cardiomyopathy (HCM) is the most common genetic cardiovascular disease. Although some genes and miRNAs related with HCM have been studied, the molecular regulatory mechanisms between miRNAs and transcription factors (TFs) in HCM have not been systematically elucidated. In this study, we proposed a novel method for identifying dysregulated miRNA‐TF feed‐forward loops (FFLs) by integrating sample matched miRNA and gene expression profiles and experimentally verified interactions of TF‐target gene and miRNA‐target gene. We identified 316 dysregulated miRNA‐TF FFLs in HCM, which were confirmed to be closely related with HCM from various perspectives. Subpathway enrichment analysis demonstrated that the method was outperformed by the existing method. Furthermore, we systematically analysed the global architecture and feature of gene regulation by miRNAs and TFs in HCM, and the FFL composed of hsa‐miR‐17‐5p, FASN and STAT3 was inferred to play critical roles in HCM. Additionally, we identified two panels of biomarkers defined by three TFs (CEBPB, HIF1A, and STAT3) and four miRNAs (hsa‐miR‐155‐5p, hsa‐miR‐17‐5p, hsa‐miR‐20a‐5p, and hsa‐miR‐181a‐5p) in a discovery cohort of 126 samples, which could differentiate HCM patients from healthy controls with better performance. Our work provides HCM‐related dysregulated miRNA‐TF FFLs for further experimental study, and provides candidate biomarkers for HCM diagnosis and treatment.

Gene regulation networks contain recurring circuit patterns called network motifs. One of the most common network motif is the incoherent type 1 feed‐forward loop (I1‐FFL), in which an activator controls both gene and repressor of that gene. This motif was shown to act as a pulse generator and response accelerator of gene expression. Here we consider an additional function of this motif: the I1‐FFL can generate a non‐monotonic dependence of gene expression on the input signal. Here, we study this experimentally in the galactose system of Escherichia coli , which is regulated by an I1‐FFL. The promoter activity of two of the gal operons, galETK and galP , peaks at intermediate levels of the signal cAMP. We find that mutants in which the I1‐FFL is disrupted lose this non‐monotonic behavior, and instead display monotonic input functions. Theoretical analysis suggests that non‐monotonic input functions can be achieved for a wide range of parameters by the I1‐FFL. The models also suggest regimes where a monotonic input‐function can occur, as observed in the mglBAC operon regulated by the same I1‐FFL. The present study thus experimentally demonstrates how upstream circuitry can affect gene input functions and how an I1‐FFL functions within its natural context in the cell.

Summary Insulin/IGF-1-like signalling (IIS) and dietary restriction (DR) are the two major modulatory pathways controlling longevity across species. Here, we show that both pathways license a common chromatin modifier, ZFP-1/AF10. The downstream transcription factors of the IIS and select DR pathways, DAF-16/FOXO or PHA-4/FOXA, respectively, both transcriptionally regulate the expression of zfp-1. ZFP-1, in turn, negatively regulates the expression of DAF-16/FOXO and PHA-4/FOXA target genes, apparently forming feed-forward loops that control the amplitude as well as the duration of gene expression. We show that ZFP-1 mediates this regulation by negatively influencing the recruitment of DAF-16/FOXO and PHA-4/FOXA to their target promoters. Consequently, zfp-1 is required for the enhanced longevity observed during DR and on knockdown of IIS. Our data reveal how two distinct sensor pathways control an overlapping set of genes, using different downstream transcription factors, integrating potentially diverse and temporally distinct nutritional situations.

The eukaryotic cell cycle requires precise temporal coordination of the activities of hundreds of ‘executor’ proteins (EPs) involved in cell growth and division. Cyclin‐dependent protein kinases (Cdks) play central roles in regulating the production, activation, inactivation and destruction of these EPs. From genome‐scale data sets of budding yeast, we identify 126 EPs that are regulated by Cdk1 both through direct phosphorylation of the EP and through phosphorylation of the transcription factors that control expression of the EP, so that each of these EPs is regulated by a feed‐forward loop (FFL) from Cdk1. By mathematical modelling, we show that such FFLs can activate EPs at different phases of the cell cycle depending of the effective signs (+ or −) of the regulatory steps of the FFL. We provide several case studies of EPs that are controlled by FFLs exactly as our models predict. The signal‐transduction properties of FFLs allow one (or a few) Cdk signal(s) to drive a host of cell cycle responses in correct temporal sequence. Proteins that are periodically synthesized during the cell cycle are often dual‐regulated by cyclin‐dependent kinase: by direct phosphorylation of the protein itself and by phosphorylation of its transcription factor. This ‘feed‐forward loop’ topology can transduce a periodic cycle of Cdk activity into four distinct waves of ‘executor protein’ activity: robust executor protein activity at low Cdk levels (G1), a pulse of activity when Cdk activity raises (G1/S transition), robust activity at high Cdk levels (S/G2/M), or a pulse when Cdk activity declines (mitotic exit). Prediction from these feed‐forward loops on cell cycle timing are in several cases supported by experimental evidence and lead to testable hypotheses in others.

Recent findings show that single, non-neuronal cells are also able to learn signalling responses developing cellular memory. In cellular learning nodes of signalling networks strengthen their interactions e.g. by the conformational memory of intrinsically disordered proteins, protein translocation, miRNAs, lncRNAs, chromatin memory and signalling cascades. This can be described by a generalized, unicellular Hebbian learning process, where those signalling connections, which participate in learning, become stronger. Here we review those scenarios, where cellular signalling is not only repeated in a few times (when learning occurs), but becomes too frequent, too large, or too complex and overloads the cell. This leads to desensitisation of signalling networks by decoupling signalling components, receptor internalization, and consequent downregulation. These molecular processes are examples of anti-Hebbian learning and ‘forgetting’ of signalling networks. Stress can be perceived as signalling overload inducing the desensitisation of signalling pathways. Ageing occurs by the summative effects of cumulative stress downregulating signalling. We propose that cellular learning desensitisation, stress and ageing may be placed along the same axis of more and more intensive (prolonged or repeated) signalling. We discuss how cells might discriminate between repeated and unexpected signals, and highlight the Hebbian and anti-Hebbian mechanisms behind the fold-change detection in the NF- κ B signalling pathway. We list drug design methods using Hebbian learning (such as chemically-induced proximity) and clinical treatment modalities inducing (cancer, drug allergies) desensitisation or avoiding drug-induced desensitisation. A better discrimination between cellular learning, desensitisation and stress may open novel directions in drug design, e.g. helping to overcome drug resistance.

Hfq (host factor for phage Q beta) is key for posttranscriptional gene regulation in many bacteria. Hfq’s function is to stabilize sRNAs and to facilitate base-pairing with trans-encoded target mRNAs. Loss of Hfq typically results in pleiotropic phenotypes, and, in the major human pathogen Vibrio cholerae, Hfq inactivation has been linked to reduced virulence, failure to produce biofilms, and impaired intercellular communication. However, the RNA ligands of Hfq in V. cholerae are currently unknown. Here, we used RIP-seq (RNA immunoprecipitation followed by high-throughput sequencing) analysis to identify Hfq-bound RNAs in V. cholerae. Our work revealed 603 coding and 85 noncoding transcripts associated with Hfq, including 44 sRNAs originating from the 3′ end of mRNAs. Detailed investigation of one of these latter transcripts, named FarS (fatty acid regulated sRNA), showed that this sRNA is produced by RNase E-mediated maturation of the fabB 3′UTR, and, together with Hfq, inhibits the expression of two paralogous fadE mRNAs. The fabB and fadE genes are antagonistically regulated by the major fatty acid transcription factor, FadR, and we show that, together, FadR, FarS, and FadE constitute a mixed feed-forward loop regulating the transition between fatty acid biosynthesis and degradation in V. cholerae. Our results provide the molecular basis for studies on Hfq in V. cholerae and highlight the importance of a previously unrecognized sRNA for fatty acid metabolism in this major human pathogen.

The plant kingdom produces hundreds of thousands of specialized bioactive metabolites, some with pharmaceutical and biotechnological importance. Their biosynthesis and function have been studied for decades, but comparatively less is known about how transcription factors with overlapping functions and contrasting regulatory activities coordinately control the dynamics and output of plant specialized metabolism. Here, we performed temporal studies on pathogen-infected intact host plants with perturbed transcription factors. We identified WRKY33 as the condition-dependent master regulator and MYB51 as the dual functional regulator in a hierarchical gene network likely responsible for the gene expression dynamics and metabolic fluxes in the camalexin and 4-hydroxy-indole-3-carbonylnitrile (4OH-ICN) pathways. This network may have also facilitated the regulatory capture of the newly evolved 4OH-ICN pathway in by the more-conserved transcription factor MYB51. It has long been held that the plasticity of plant specialized metabolism and the canalization of development should be differently regulated; our findings imply a common hierarchical regulatory architecture orchestrated by transcription factors for specialized metabolism and development, making it an attractive target for metabolic engineering.