Biological systems are generally complicated and/or complex. In the former approach, one sets up a model with a large number of parameters to describe the system in detail. The latter approach focuses on understanding the universal aspects of biological systems. In this case, an appropriate simple model represents a universality class. The extraction of universal properties is supported by evolutionary robustness and the reduction of dimensionality in high-dimensional states. Integrating the data-driven omics approach with the universality approach is an important step in systems biology.
The mitochondrial (mt) genomes of animals, including humans, are typically a single circular chromosome containing all mt genes. In several animal lineages, however, mt genomes have become fragmented, with genes distributed on multiple minichromosomes. How fragmented mt genomes are transcribed is still poorly understood. In this study, we investigated the transcription of the extensively fragmented mt genomes of the human head louse (<i>Pediculus humanus capitis</i>) and the human body louse (<i>Pediculus humanus corporis</i>). RNA-seq reads of both subspecies were retrieved from the NCBI Sequence Read Archive database and mapped to their mt genomes. The transcription level of each mt gene, minichromosome, motif, coding region and non-coding region, measured by RPKM (Reads Per Kilobase of transcript per Million mapped reads), TPM (Transcripts Per Million) or read coverage, was analysed statistically. In both subspecies, mt minichromosomes were transcribed entirely, with coding regions transcribed at much higher levels than non-coding regions. The 37 mt genes are transcribed unevenly, with <i>rrnL</i>, <i>cox1</i>, <i>cox2</i>, <i>cox3</i> and <i>atp6</i> transcribed at significantly higher levels than several other genes. Many transcription events terminate near a GC-rich motif in the non-coding regions; however, some transcription events pass this motif, leading to the transcription of entire non-coding regions. Despite the drastic difference in mt genome organisation, the human lice share several transcriptional features with humans, but also have unique features related to their fragmented mt genome organisation. The current study represents the first effort into the transcription of fragmented mt genomes. As more RNA-seq data become available, further studies on other animals with fragmented mt genomes are necessary to fully understand how genome fragmentation affects transcription.
Abstract Piezo1 plays a key role in the immune response during sepsis. To date, our understanding of the role of Piezo1 in inflammatory diseases has mostly been limited to influencing vasomotor function and regulating inflammatory infiltration. Whether and how Piezo1 in macrophages is involved in developing septic cardiac dysfunction has never been explored. Here, we have successfully established a mouse model with myeloid cell-specific knockdown of Piezo1. The intraperitoneal injection of lipopolysaccharide (LPS) resulted in a significant increase in cardiac macrophage infiltration, as well as an increase in the expression of inflammatory factors and the inflammatory response. However, myeloid cell-specific knockdown of Piezo1 impaired this response, leading to an increase in macrophage polarization towards the M2 type and the decreased inflammatory response. As a result, myocardial injury caused by sepsis was attenuated. We have also demonstrated that the PI3K/AKT pathway is significantly activated after Piezo1 knockdown, resulting in reduced myocardial dysfunction. Our data indicate that myeloid cell-specific knockdown of Piezo1 can influence macrophage polarization and thus exert cardioprotective effects in a murine model of sepsis, providing potential ideas and targets for the treatment of infectious cardiac dysfunction.
Geoffrey Wilson, Peter M. Groffman, Lisa D. Martel
et al.
Identifying which aspects of global environmental change are driving observed ecosystem process responses is a great challenge. Here, we address how long-term (10–25 years) alterations in soil moisture, and nitrogen (N) oligotrophication (i.e., decreases in soil N availability relative to plant demand), alter the production of plant-available N via net mineralization and nitrification in a northern hardwood forest. Our objectives were to determine whether soil moisture has changed over the past decade and whether N cycle processes have become less sensitive to soil moisture over time due to N oligotrophication. We used long-term datasets from several related studies to show (i) increasing winter soil temperatures and declining summer soil moisture from late 2010 into 2024, (ii) reductions in sensitivity of N cycling rates to soil moisture, and (iii) declining moisture-adjusted N cycle processes (the ratio of rate of N process:soil moisture) over time in both summer and winter. These changes suggest continued reductions in N availability to plants in these forests, with potential effects on forest productivity and response to disturbance.
AlphaFold 3 represents a transformative advancement in computational biology, enhancing protein structure prediction through novel multi-scale transformer architectures, biologically informed cross-attention mechanisms, and geometry-aware optimization strategies. These innovations dramatically improve predictive accuracy and generalization across diverse protein families, surpassing previous methods. Crucially, AlphaFold 3 embodies a paradigm shift toward differentiable simulation, bridging traditional static structural modeling with dynamic molecular simulations. By reframing protein folding predictions as a differentiable process, AlphaFold 3 serves as a foundational framework for integrating deep learning with physics-based molecular
Janine Wesslowski, Sadia Safi, Michelle Rottmann
et al.
Upon engagement of one of the nineteen secreted Wnt signaling proteins with one of the ten Frizzled transmembrane Wnt receptors (FZD<sub>1–10</sub>), a wide variety of cellular Wnt signaling responses can be elicited, the selectivity of which depends on the following: (1) the specific Wnt-FZD pairing, (2) the participation of Wnt co-receptors and (3) the cellular context. Co-receptors play a pivotal role in guiding the specificity of Wnt signaling, most notably between β-catenin-dependent and -independent pathways, where co-receptors such as LRP5/6 and ROR1/2/PTK7 play major roles, respectively. It remains less understood how specific Wnt/FZD combinations contribute to the selectivity of downstream Wnt signaling, and we lack accurate comparative data on their binding properties under physiological conditions. Here, using fluorescently tagged Wnt3a, Wnt5a and Wnt16 proteins and cell lines expressing HiBiT-tagged Frizzled, we build on our ongoing efforts to provide a complete overview of the biophysical properties of all Wnt/FZD interactions using full-length proteins. Our real-time NanoBRET analysis using living cells expressing low receptor levels provides more accurate quantification of binding and will help us understand how these binary engagements control Wnt signaling outputs. We also provide evidence that LRP6 regulates the binding affinity of Wnt/FZD interactions in the trimeric Wnt-FZD-LRP6 complex.
In this paper, we propose and study several inverse problems of determining unknown parameters in nonlocal nonlinear coupled PDE systems, including the potentials, nonlinear interaction functions and time-fractional orders. In these coupled systems, we enforce non-negativity of the solutions, aligning with realistic scenarios in biology and ecology. There are several salient features of our inverse problem study: the drastic reduction in measurement/observation data due to averaging effects, the nonlinear coupling between multiple equations, and the nonlocality arising from fractional-type derivatives. These factors present significant challenges to our inverse problem, and such inverse problems have never been explored in previous literature. To address these challenges, we develop new and effective schemes. Our approach involves properly controlling the injection of different source terms to obtain multiple sets of mean flux data. This allows us to achieve unique identifiability results and accurately determine the unknown parameters. Finally, we establish a connection between our study and practical applications in biology, further highlighting the relevance of our work in real-world contexts.
Sylvain Thierry, Sarah Maadadi, Aurore Berton
et al.
Toll-like receptor 3 (TLR3) is an innate immune receptor that recognizes double-stranded RNA (dsRNA) and induces inflammation in immune and normal cells to initiate anti-microbial responses. TLR3 acts also as a death receptor only in cancer cells but not in their normal counterparts, making it an attractive target for cancer therapies. To date, all of the TLR3-activating dsRNAs used at preclinical or clinical stages have major drawbacks such as structural heterogeneity, toxicity, and lack of specificity and/or efficacy. We conducted the discovery process of a new family of TLR3 agonists that are chemically manufactured on solid-phase support and perfectly defined in terms of sequence and size. A stepwise discovery process was performed leading to the identification of TL-532, a 70 base pair dsRNA that is potent without transfection reagent and is highly specific for TLR3 without activating other innate nucleic sensors such as RIG-I/MDA5, TLR7, TLR8, and TLR9. TL-532 induces inflammation in murine RAW264.7 myeloid macrophages, in human NCI-H292 lung cancer cells, and it promotes immunogenic apoptosis in tumor cells in vitro and ex vivo without toxicity towards normal primary cells. In conclusion, we identified a novel TLR3 agonist called TL-532 that has promising anticancer properties.
Laia Cuesta-Casanovas, Jennifer Delgado-Martínez, Josep M. Cornet-Masana
et al.
Abstract Background Development of precision medicine requires the identification of easily detectable and druggable biomarkers. Despite recent targeted drug approvals, prognosis of acute myeloid leukemia (AML) patients needs to be greatly improved, as relapse and refractory disease are still difficult to manage. Thus, new therapeutic approaches are needed. Based on in silico-generated preliminary data and the literature, the role of the prolactin (PRL)-mediated signaling was interrogated in AML. Methods Protein expression and cell viability were determined by flow cytometry. Repopulation capacity was studied in murine xenotransplantation assays. Gene expression was measured by qPCR and luciferase-reporters. SA-β-Gal staining was used as a senescence marker. Results The prolactin receptor (PRLR) was upregulated in AML cells, as compared to their healthy counterpart. The genetic and molecular inhibition of this receptor reduced the colony-forming potential. Disruption of the PRLR signaling, either using a mutant PRL or a dominant-negative isoform of PRLR, reduced the leukemia burden in vivo, in xenotransplantation assays. The expression levels of PRLR directly correlated with resistance to cytarabine. Indeed, acquired cytarabine resistance was accompanied with the induction of PRLR surface expression. The signaling associated to PRLR in AML was mainly mediated by Stat5, in contrast to the residual function of Stat3. In concordance, Stat5 mRNA was significantly overexpressed at mRNA levels in relapse AML samples. A senescence-like phenotype, measured by SA-β-gal staining, was induced upon enforced expression of PRLR in AML cells, partially dependent on ATR. Similar to the previously described chemoresistance-induced senescence in AML, no cell cycle arrest was observed. Additionally, the therapeutic potential of PRLR in AML was genetically validated. Conclusions These results support the role of PRLR as a therapeutic target for AML and the further development of drug discovery programs searching for specific PRLR inhibitors.
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Cytology
Skeletal muscle is a pivotal organ in humans that maintains locomotion and homeostasis. Muscle atrophy caused by sarcopenia and cachexia, which results in reduced muscle mass and impaired skeletal muscle function, is a serious health condition that decreases life longevity in humans. Recent studies have revealed the molecular mechanisms by which long non-coding RNAs (lncRNAs) regulate skeletal muscle mass and function through transcriptional regulation, fiber-type switching, and skeletal muscle cell proliferation. In addition, lncRNAs function as natural inhibitors of microRNAs and induce muscle hypertrophy or atrophy. Intriguingly, muscle atrophy modifies the expression of thousands of lncRNAs. Therefore, although their exact functions have not yet been fully elucidated, various novel lncRNAs associated with muscle atrophy have been identified. Here, we comprehensively review recent knowledge on the regulatory roles of lncRNAs in skeletal muscle atrophy. In addition, we discuss the issues and possibilities of targeting lncRNAs as a treatment for skeletal muscle atrophy and muscle wasting disorders in humans.
Cellular heterogeneity is an immanent property of biological systems that covers very different aspects of life ranging from genetic diversity to cell-to-cell variability driven by stochastic molecular interactions, and noise induced cell differentiation. Here, we review recent developments in characterizing cellular heterogeneity by distributions and argue that understanding multicellular life requires the analysis of heterogeneity dynamics at single cell resolution by integrative approaches that combine methods from non-equilibrium statistical physics, information theory and omics biology.
Abstract Yaks are typical plateau-adapted animals, however the microvascular changes and characteristics in their lungs after birth are still unclear. Pulmonary microvasculature characteristics and changes across age groups were analysed using morphological observation and molecular biology detection in yaks aged 1, 30 and 180 days old in addition to adults. Results: Our experiments demonstrated that yaks have fully developed pulmonary alveolar at birth but that interalveolar thickness increased with age. Immunofluorescence observations showed that microvessel density within the interalveolar septum in the yak gradually increased with age. In addition, transmission electron microscopy (TEM) results showed that the blood–air barrier of 1-day old and 30-days old yaks was significantly thicker than that observed at 180-days old and in adults (P < 0.05), which was caused by the thinning of the membrane of alveolar epithelial cells. Furthermore, Vegfa and Epas1 expression levels in 30-day old yaks were the highest in comparison to the other age groups (P < 0.05), whilst levels in adult yaks were the lowest (P < 0.05). The gradual increase in lung microvessel density can effectively satisfy the oxygen requirements of ageing yaks. In addition, these results suggest that the key period of yak lung development is from 30 to 180 days.
Annie Cristhine Moraes Sousa-Squiavinato, Renata Ivo Vasconcelos, Adriana Sartorio Gehren
et al.
Abstract Background Colorectal cancer (CRC) is among the deadliest cancers, wherein early dissemination of tumor cells, and consequently, metastasis formation, are the main causes of mortality and poor prognosis. Cofilin-1 (CFL-1) and its modulators, LIMK1/SSH1, play key roles in mediating the invasiveness by driving actin cytoskeleton reorganization in various cancer types. However, their clinical significance and prognostic value in CRC has not been fully explored. Here, we evaluated the clinical contribution of these actin regulators according to TNM and consensus molecular subtypes (CMSs) classification. Methods CFL-1, LIMK1 and SSH1 mRNA/protein levels were assessed by real-time PCR and immunohistochemical analyses using normal adjacent and tumor tissues obtained from a clinical cohort of CRC patients. The expression levels of these proteins were associated with clinicopathological features by using the chi square test. In addition, using RNA-Seq data of CRC patients from The Cancer Genome Atlas (TCGA) database, we determine how these actin regulators are expressed and distributed according to TNM and CMSs classification. Based on gene expression profiling, Kaplan–Meier survival analysis was used to evaluated overall survival. Results Bioinformatic analysis revealed that LIMK1 expression was upregulated in all tumor stages. Patients with high levels of LIMK1 demonstrated significantly lower overall survival rates and exhibited greater lymph node metastatic potential in a clinical cohort. In contrast, CFL-1 and SSH1 have expression downregulated in all tumor stages. However, immunohistochemical analyses showed that patients with high protein levels of CFL-1 and SSH1 exhibited greater lymph node metastatic potential and greater depth of local invasion. In addition, using the CMSs classification to evaluate different biological phenotypes of CRC, we observed that LIMK1 and SSH1 genes are upregulated in immune (CMS1) and mesenchymal (CMS4) subtypes. However, patients with high levels of LIMK1 also demonstrated significantly lower overall survival rates in canonical (CMS2), and metabolic (CMS3) subtypes. Conclusions We demonstrated that CFL-1 and its modulators, LIMK1/SSH1, are differentially expressed and associated with lymph node metastasis in CRC. Finally, this expression profile may be useful to predict patients with aggressive signatures, particularly, the immune and mesenchymal subtypes of CRC.
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Cytology
Though it goes without saying that linear algebra is fundamental to mathematical biology, polynomial algebra is less visible. In this article, we will give a brief tour of four diverse biological problems where multivariate polynomials play a central role -- a subfield that is sometimes called "algebraic biology." Namely, these topics include biochemical reaction networks, Boolean models of gene regulatory networks, algebraic statistics and genomics, and place fields in neuroscience. After that, we will summarize the history of discrete and algebraic structures in mathematical biology, from their early appearances in the late 1960s to the current day. Finally, we will discuss the role of algebraic biology in the modern classroom and curriculum, including resources in the literature and relevant software. Our goal is to make this article widely accessible, reaching the mathematical biologist who knows no algebra, the algebraist who knows no biology, and especially the interested student who is curious about the synergy between these two seemingly unrelated fields.
{\it Caenorhabditis elegans} nematode worms are the only animals with the known detailed neural connectivity diagram, well characterized genomics, and relatively simple quantifiable behavioral output. With this in mind, many researchers view this animal as the best candidate for a systems biology approach, where one can integrate molecular and cellular knowledge to gain global understanding of worm's behavior. This work reviews some research in this direction, emphasizing computational perspective, and points out some successes and challenges to meet this lofty goal.
Abstract A mounting body of the literature suggests that environmental chemicals found in food and water could affect female reproduction. Many worldwide daily-used products have been shown to contain chemicals that could incur adverse reproductive outcomes in the perinatal/neonatal periods, childhood, adolescence, and even adulthood. The potential impact of Bisphenol A (BPA), Phthalates and Perfluoroalkyl substances (PFAS) on female reproduction, in particular on puberty, PCOS pathogenesis, infertility, ovarian function, endometriosis, and recurrent pregnancy loss, in both humans and animals, will be discussed in this report in order to provide greater clinician and public awareness about the potential consequences of these chemicals. The effects of these substances could interfere with hormone biosynthesis/action and could potentially be transmitted to further generations. Thus proper education about these chemicals can help individuals decide to limit exposure, ultimately alleviating the risk on future generations.
Adrià Pérez, Gerard Martínez-Rosell, Gianni De Fabritiis
Classical molecular dynamics (MD) simulations will be able to reach sampling in the second timescale within five years, producing petabytes of simulation data at current force field accuracy. Notwithstanding this, MD will still be in the regime of low-throughput, high-latency predictions with average accuracy. We envisage that machine learning (ML) will be able to solve both the accuracy and time-to-prediction problem by learning predictive models using expensive simulation data. The synergies between classical, quantum simulations and ML methods, such as artificial neural networks, have the potential to drastically reshape the way we make predictions in computational structural biology and drug discovery.
Emmanouil Dokianakis, Nikolaos Tsirigotakis, Vasiliki Christodoulou
et al.
Abstract Background Phlebotomine sand flies (Diptera: Psychodidae) are vectors of Leishmania spp., protozoan parasites responsible for a group of neglected diseases called leishmaniases. Two sand fly genera, Phlebotomus and Sergentomyia, contain species that are present in the Mediterranean islands of Crete and Cyprus where the visceral (VL), cutaneous (CL) and canine (CanLei) leishmaniases are a public health concern. The risk of transmission of different Leishmania species can be studied in an area by monitoring their vectors. Sand fly species are traditionally identified using morphological characteristics but minute differences between individuals or populations could be overlooked leading to wrong epidemiological predictions. Molecular identification of these important vectors has become, therefore, an essential tool for research tasks concerning their geographical distribution which directly relates to leishmaniasis control efforts. DNA barcoding is a widely used molecular identification method for cataloguing animal species by sequencing a fragment of the mitochondrial gene encoding cytochrome oxidase I. Results DNA barcoding was used to identify individuals of five sand fly species (Phlebotomus papatasi, P. similis, P. killicki, Sergentomyia minuta, S. dentata) circulating in the islands of Crete and Cyprus during the years 2011–2014. Phlebotomus papatasi is a known vector of zoonotic CL in the Middle East and it is found in both islands. Phlebotomus similis is the suspected vector of Leishmania tropica in Greece causing anthroponotic CL. Phlebotomus killicki was collected in Cyprus for the first time. Sergentomyia minuta, found to present intraspecific diversity, is discussed for its potential as a Leishmania vector. Molecular identification was consistent with the morphological identification. It successfully identified males and females, which is difficult when using only morphological characters. A phylogenetic tree was constructed based on the barcodes acquired, representing their genetic relationships along with other species from the area studied. All individuals identified were clustered according to their species and subgenus. Conclusions Molecular identification of sand flies via DNA barcoding can accurately identify these medically important insects assisting traditional morphological tools, thus helping to assess their implication in Leishmania transmission.