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The search for chemical hit material is a lengthy and increasingly expensive drug discovery process. To improve it, ligand-based quantitative structure-activity relationship models have been broadly applied to optimize primary and secondary compound properties. Although these models can be deployed as early as the stage of molecule design, they have a limited applicability domain─if the structures of interest differ substantially from the chemical space on which the model was trained, a reliable prediction will not be possible. Image-informed ligand-based models partly solve this shortcoming by focusing on the phenotype of a cell caused by small molecules, rather than on their structure. While this enables chemical diversity expansion, it limits the application to compounds physically available and imaged. Here, we employ an active learning approach to capitalize on both of these methods' strengths and boost the model performance of a mitochondrial toxicity assay (Glu/Gal). Specifically, we used a phenotypic Cell Painting screen to build a chemistry-independent model and adopted the results as the main factor in selecting compounds for experimental testing. With the additional Glu/Gal annotation for selected compounds we were able to dramatically improve the chemistry-informed ligand-based model with respect to the increased recognition of compounds from a 10% broader chemical space.

With more and more data being collected, modern network representations exploit the complementary nature of different data sources as well as similarities across patients. We here introduce the Variation of information fused Layers of Networks algorithm (ViLoN), a novel network-based approach for the integration of multiple molecular profiles. As a key innovation, it directly incorporates prior functional knowledge (KEGG, GO). In the constructed network of patients, patients are represented by networks of pathways, comprising genes that are linked by common functions and joint regulation in the disease. Patient stratification remains a key challenge both in the clinic and for research on disease mechanisms and treatments. We thus validated ViLoN for patient stratification on multiple data type combinations (gene expression, methylation, copy number), showing substantial improvements and consistently competitive performance for all. Notably, the incorporation of prior functional knowledge was critical for good results in the smaller cohorts (rectum adenocarcinoma: 90, esophageal carcinoma: 180), where alternative methods failed., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Tendinopathies are painful, disabling conditions that afflict 25% of the adult human population. Filling an unmet need for realistic large-animal models, we here present an ovine model of tendon injury for the comparative study of adult scarring repair and fetal regeneration. Complete regeneration of the fetal tendon within 28 days is demonstrated, while adult tendon defects remained macroscopically and histologically evident five months post-injury. In addition to a comprehensive histological assessment, proteome analyses of secretomes were performed. Confirming histological data, a specific and pronounced inflammation accompanied by activation of neutrophils in adult tendon defects was observed, corroborated by the significant up-regulation of pro-inflammatory factors, neutrophil attracting chemokines, the release of potentially tissue-damaging antimicrobial and extracellular matrix-degrading enzymes, and a response to oxidative stress. In contrast, secreted proteins of injured fetal tendons included proteins initiating the resolution of inflammation or promoting functional extracellular matrix production. These results demonstrate the power and relevance of our novel ovine fetal tendon regeneration model, which thus promises to accelerate research in the field. First insights from the model already support our molecular understanding of successful fetal tendon healing processes and may guide improved therapeutic strategies.

Objective: To assess gene expression in cardiomyocytes isolated from patients with aortic stenosis, hypothesizing that maladaptive remodeling and inflammation-related genes are higher in male vs female patients., Patients and Methods: In this study, 34 patients with aortic stenosis undergoing aortic valve replacement from March 20, 2016, through May 24, 2017, at the German Heart Centre in Berlin, Germany, were included. Isolated cardiomyocytes from interventricular septum samples were used for gene expression analysis. Clinical and echocardiographic data were collected preoperatively., Results: Age, body mass index, systolic and diastolic blood pressure, comorbidities, and medication were similar between the 17 male and 17 female patients. The mean ± SD left ventricular end-diastolic diameter (52±9 vs 45±4 mm; P=.007) and posterior wall thickness (14.2±2.5 vs 12.1±1.6 mm; P=.03) were higher in male vs female patients, while ejection fraction was lower in male patients (49%±14% vs 59%±5%; P=.01). Focusing on structural genes involved in the development of cardiac hypertrophy and remodeling, we found that most were expressed higher in male vs female patients. Our modeling analysis revealed that 2 inflammation-related genes, CCN2 and NFKB1, were negatively related to ejection fraction, with this effect being male specific (P=.03 and P=.02, respectively)., Conclusion: These findings provide novel insight into cardiomyocyte-specific molecular changes related to sex differences in pressure overload and a significant male-specific association between cardiac function and inflammation-related genes. Considering these sex differences may contribute toward a more accurate design of research and the development of more appropriate therapeutic approaches for both male and female patients., (Copyright © 2019 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Multipotent Nkx2-1-positive lung epithelial primordial progenitors of the foregut endoderm are thought to be the developmental precursors to all adult lung epithelial lineages. However, little is known about the global transcriptomic programs or gene networks that regulate these gateway progenitors in vivo. Here we use bulk RNA-sequencing to describe the unique genetic program of in vivo murine lung primordial progenitors and computationally identify signaling pathways, such as Wnt and Tgf-β superfamily pathways, that are involved in their cell-fate determination from pre-specified embryonic foregut. We integrate this information in computational models to generate in vitro engineered lung primordial progenitors from mouse pluripotent stem cells, improving the fidelity of the resulting cells through unbiased, easy-to-interpret similarity scores and modulation of cell culture conditions, including substratum elastic modulus and extracellular matrix composition. The methodology proposed here can have wide applicability to the in vitro derivation of bona fide tissue progenitors of all germ layers.

Osteoarthritis (OA), a degenerative joint disease characterized by progressive cartilage degeneration, is one of the leading causes of disability worldwide owing to the limited regenerative capacity of adult articular cartilage. Currently, there are no disease-modifying pharmacological or surgical therapies for OA. Fetal mammals, in contrast to adults, are capable of regenerating injured cartilage in the first two trimesters of gestation. A deeper understanding of the properties intrinsic to the response of fetal tissue to injury would allow us to modulate the way in which adult tissue responds to injury. In this study, we employed secretome proteomics to compare fetal and adult protein regulation in response to cartilage injury using an ovine cartilage defect model. The most relevant events comprised proteins associated with the immune response and inflammation, proteins specific for cartilage tissue and cartilage development, and proteins involved in cell growth and proliferation. Alarmins S100A8, S100A9 and S100A12 and coiled-coil domain containing 88A (CCDC88A), which are associated with inflammatory processes, were found to be significantly upregulated following injury in adult, but not in fetal animals. By contrast, cartilage-specific proteins like proteoglycan 4 were upregulated in response to injury only in fetal sheep postinjury. Our results demonstrate the power and relevance of the ovine fetal cartilage regeneration model presented here for the first time. The identification of previously unrecognized modulatory proteins that plausibly affect the healing process holds great promise for potential therapeutic interventions., Competing Interests: Competing interestsThe authors declare no competing or financial interests., (© 2018. Published by The Company of Biologists Ltd.)

Chinese Hamster Ovary (CHO) cells are the preferred cell line for production of biopharmaceuticals. These cells are capable to grow without serum supplementation, but drastic changes in their phenotype occur during adaptation to protein-free growth, which typically include the change to a suspension phenotype with reduced growth rate. A possible approach to understand this transformation, with the intention to counteract the reduction in growth by targeted supplementation of protein-free media, is gene expression profiling. The increasing availability of genome-scale data for CHO now facilitates quests for a better understanding of metabolic pathways and gene networks. So far, systematic large-scale expression profiling in CHO cells by microarray was limited due to lack of publicly available array designs and limitations of alternative approaches. Based on the recent release of CHO and Chinese Hamster genome sequences, including an annotated RefSeq genome, we have constructed a publicly available microarray design for effective genome-scale expression profiling. The design employed microarray probes optimized for uniformity, sensitivity, and specificity, with probe properties computed using the latest thermodynamic models. We validated the platform in an analysis of gene expression changes in response to serum-free adaptation. The observed effects on the lipid metabolism as well as on nucleotide synthesis were used to successfully select media supplements that were able to increase growth rate., (Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.)

The clinical importance of anterior foregut endoderm (AFE) derivatives, such as thyrocytes, has led to intense research efforts for their derivation through directed differentiation of pluripotent stem cells (PSCs). Here, we identify transient overexpression of the transcription factor (TF) NKX2-1 as a powerful inductive signal for the robust derivation of thyrocyte-like cells from mouse PSC-derived AFE. This effect is highly developmental stage specific and dependent on FOXA2 expression levels and precise modulation of BMP and FGF signaling. The majority of the resulting cells express thyroid TFs (Nkx2-1, Pax8, Foxe1, Hhex) and thyroid hormone synthesis-related genes (Tg, Tpo, Nis, Iyd) at levels similar to adult mouse thyroid and give rise to functional follicle-like epithelial structures in Matrigel culture. Our findings demonstrate that NKX2-1 overexpression converts AFE to thyroid epithelium in a developmental time-sensitive manner and suggest a general methodology for manipulation of cell-fate decisions of developmental intermediates., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

High-throughput technologies, such as next-generation sequencing, have turned molecular biology into a data-intensive discipline, requiring bioinformaticians to use high-performance computing resources and carry out data management and analysis tasks on large scale. Workflow systems can be useful to simplify construction of analysis pipelines that automate tasks, support reproducibility and provide measures for fault-tolerance. However, workflow systems can incur significant development and administration overhead so bioinformatics pipelines are often still built without them. We present the experiences with workflows and workflow systems within the bioinformatics community participating in a series of hackathons and workshops of the EU COST action SeqAhead. The organizations are working on similar problems, but we have addressed them with different strategies and solutions. This fragmentation of efforts is inefficient and leads to redundant and incompatible solutions. Based on our experiences we define a set of recommendations for future systems to enable efficient yet simple bioinformatics workflow construction and execution.