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Results for “synthetic biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2026

ENPP3 expressed by HER2-positive breast cancer cells is associated with good prognosis by restraining epithelial-to-mesenchymal phenotype

Background Ectonucleotide pyrophosphatase/phosphodiesterase 3 (ENPP3/CD203c) is largely studied as a marker of mast cells and basophils. By depleting extracellular ATP, it prevents excessive activation of mast cells and basophils, hence reducing inflammation and allergic reactions. Recent findings have also shown that Enpp3 can deplete cGAMP, another molecule involved in STING activation and IFN-mediated pro-inflammation. Little is still known regarding the role of Enpp3 in non-immune cells although a few reports have described its expression in healthy tissues and tumors. Methods In silico analysis were performed to investigate the expression levels and the prognostic value of Enpp3 in breast cancer, together with ovarian, prostate and colon carcinoma. ENPP3 expression was evaluated in formalin-fixed, paraffin-embedded tumor samples of breast cancer patients by immunohistochemistry, and in mouse mammary cancer cell lines by western blots. Cells were treated with EGFR ligands to stimulate the EGFR/HER2 axis. A mouse-derived mammary cancer cell line was engineered by CRISPR/Cas9 to introduce a GFP sequence under the control of the Enpp3 promoter. GFP-positive and -negative cells were sorted and analyzed by gene expression profiling to identify genes and pathways associated with Enpp3 expression. Finally, wild type and Enpp3 knockout cells were injected in the fat pad of Wsh mice, which do not have mast cells, to evaluate the growth of the tumors which were further analyzed by immunohistochemistry. Results We provide evidence that HER2-positive cells express higher levels of ENPP3 in samples of breast cancer patients. Moreover, in vitro models confirmed that HER2 expression and EGFR stimulation result in up-regulation of Enpp3. We identified pathways that can concur to Enpp3 expression and showed that in vivo the absence of Enpp3 promotes tumor growth and development of tumors with a marked epithelial-to-mesenchymal phenotype. Finally, in a small cohort of HER2-positive breast cancer patients, we found that ENPP3 expression correlates with increased relapse-free survival. Conclusions Despite its potential immunosuppressive role, our findings support the notion that ENPP3 expression is promoted by HER2 in breast cancer, and that it is endowed with a positive prognostic value.

cancer biology↗

bioRxiv2026

Multiscale modelling of drug-host-pathogen interaction: quantifying drug and immune contributions to treatment response

Background and Objective: Predicting treatment outcomes in infectious diseases requires accounting for the interplay between drug effects, pathogen dynamics, and host immunity. Integrating pharmacological and immunological approaches into a single simulation environment remains a fundamental challenge in both theory and practice. We aimed to develop and validate a multiscale in silico framework coupling these processes, and to quantify their respective contributions to bacterial clearance. Methods: We present the Drug-Host-Pathogen Interaction (DHPI) framework, combining three independent mechanistic components: a physiologically based pharmacokinetic model of drug disposition, a pharmacokinetic-pharmacodynamic model of drug-induced bacterial killing, and a stochastic agent-based model of the immune response. Continuous concentration profiles are time-averaged onto the agent-based time grid, assigned to bacterial phenotypic states, and converted into per-agent killing probabilities, so that drug-mediated and immune-mediated death events are recorded separately at each step. The framework was applied to simulate symptomatic pulmonary tuberculosis. Phenotype-specific drug-efficacy parameters were inferred using Approximate Bayesian Computation from historical clinical data on eight weeks of 600 mg rifampicin monotherapy, and validated against independent early bactericidal activity data over a disjoint time window. Results: The calibrated framework reproduced the observed decline in bacterial load, and matched reported early bactericidal activity over the first week. In a virtual cohort of symptomatic patients, drug-mediated killing accounted for 81-88% and immune-mediated killing for 12-19% of total bacterial elimination over the 60-day treatment course, while the dormant, granuloma-contained fraction rose from 0.20-0.29 in the first week to 0.85-0.89 at treatment completion. Over a follow-up of up to 50 years, patients reaching clinical cure had accumulated more memory lymphocytes during treatment than those progressing to clinical failure or death; moreover, the final outcome depended on the immune changes occurring during therapy rather than on the initial disease stage. Conclusions: The results show that the DHPI framework can reproduce treatment dynamics observed in patients and enable the analysis of how therapy reshapes host immune responses and subsequent disease trajectories. By explicitly representing drug-host-pathogen interactions, it provides a mechanistic basis for in silico treatment simulations and for the study of long-term immune consequences of antimicrobial therapy.

systems biology↗

bioRxiv2026

A replicated patient-specific component of tumour telomere length across two pan-cancer cohorts

Bulk telomere length measured from tumour sequencing is routinely interpreted as a property of the cancer cells. However, a tumour specimen is a mixture, and the patient who supplies it has a telomere length of their own. Here I re-analyse published pan-cancer telomere estimates and ask how much of a tumour's telomere length is patient-specific. A calibration step comes first. Whole-genome and low-pass estimates recover the known cross-sectional attrition of leukocyte telomeres with age, at 26.6 bp per year in blood normals, whereas whole-exome estimates do not. After adjustment for cancer type, sequencing centre and sex, the exome slope is minus 0.6 bp per year. In 684 blood-normal aliquots sequenced by both assays, the whole-genome estimate declines at 38.9 bp per year, whereas the exome estimate from the same DNA shows no detectable decline. The difference between assays is 41.5 bp per year, with P = 3 x 10^-10. Because exome data constitute 78.6% of the original resource, downstream analyses use only whole-genome and low-pass libraries. Within those data, tumour telomere length tracks the patient's matched-normal telomere length. The Spearman correlation is 0.395 in TCGA, with positive associations in 22 of 23 cancer types. This finding replicates in PCAWG using a different telomere estimator, with a correlation of 0.472 and positive associations in all 24 histologies examined. Adjustment for cancer type, sequencing centre and library type leaves a regression coefficient of 0.385. The association is also stable after adjustment for age, sex, tumour purity, leukocyte fraction, ploidy, sequencing coverage and continental ancestry, with coefficients ranging from 0.406 to 0.429. Pure normal-cell admixture is rejected as the sole explanation. Under a two-compartment mixture model, the coefficient for host telomere length is expected to equal 1 and the host-by-purity interaction to equal minus 1. These restrictions are jointly rejected with P = 0.001. Tumour purity, leukocyte fraction and age each explain only about 1 to 3% of within-cohort variance and do not alter the cross-cancer ranking. By contrast, the between-cohort coefficient is not directly interpretable. Its apparent near one-to-one relationship with tissue-associated telomere length depends strongly on which tissue supplies the matched-normal reference and on the statistical spread of that predictor, falling to 0.44 when organ-matched solid tissue is used. Bulk tumour telomere length is therefore a composite phenotype containing a replicated patient-specific component. Telomere biomarker studies should include matched-normal telomere length as a covariate rather than treating tumour telomere length as exclusively tumour-intrinsic.

cancer biology↗

bioRxiv2026

Evolution and Human Neural Individuality

Individuality is a defining feature of human biology. The functional network architecture of the human brain harbors person-specific qualities and forms individualized connectivity profiles that function as a neural fingerprint, both stable and unique across time. Here, using fMRI data from 431 Human Connectome Project participants, we examined whether neural individuality is more strongly exhibited in brain regions bearing signatures of recent human evolution. We calculated region-wise fingerprinting accuracy and associated it with four properties of evolutionary cortical organization: cortical expansion, myelin content estimate (T1w/T2w), human-specific gene-expression profiles, and functional homology to other primates. Across all four measures, neural individuality was strongest in cortical areas showing greater evolutionary novelty in humans, particularly frontoparietal control and default mode networks, and weaker in more conserved primary regions. Our findings connect evolutionary variation across species with stable functional variation among individuals.

neuroscience↗

bioRxiv2026

Both environmental filtering and intraspecific variation shape small mammals' elementomes

The biogeochemical niche hypothesis (BNH) proposes the multi-elemental composition of organisms - their elementome - as a new ecological dimension. However, which ecological factors shape elementome assembly remains little known, especially in animals. Here, we studied the mandibular elementome of two sympatric small mammals - Apodemus flavicollis and Clethrionomys glareolus - to assess how intraspecific variability (ontogenetic changes in body mass and sex under the vertebrate bone hypothesis; VBH) and environmental filtering (season and habitat) shape essential and non-essential elementome assembly. Species showed moderate elementome segregation and seasonal niche partitioning, with implications for coexistence. Ontogenetic body mass predicted elemental variation and calcium substitution, with several hypermetric scalings in autumn indicating strong departures from mass-invariant homeostasis. Finally, our results suggest a dichotomy: essential elementomes were mainly driven by intraspecific variation, whereas non-essential elementomes were rather shaped by environmental filtering. Our results position animal elementomes as an integrative ecological dimension linking organismal biology, species interactions, and environmental filtering across individuals, populations, and species.

ecology↗