Search bioRxiv⌕ Search

Biology subjects

Weitz, J.

Publications and source records attributed to Weitz, J..

At least 19 recordsLinked to original sources

Systematic functional drug testing in patient-derived models reveals ex vivo sensitivities associated with clinical outcome in rare solid tumors

Rare cancers are individually uncommon but collectively represent a substantial share of cancer burden, with limited systemic treatment options for many entities. Molecular profiling identifies targetable alterations, but actionable findings are limited and responses can vary despite a matched target. This motivates complementary approaches that directly assess tumor drug response. Here, we establish a biopsy-compatible ex vivo drug sensitivity testing platform optimized for low input and reproducibility. Patient-derived material was tested either directly or following ex vivo expansion. Functional profiling was performed within clinically relevant timelines across models from 126 patients with rare advanced solid tumors. Drug responses were consistent between model types. In most samples, we identified at least one potentially active compound, supporting feasibility at biopsy-scale. High in vitro sensitivity was associated with clinical benefit and progression-free survival. These findings support functional drug sensitivity testing as a complementary component in precision oncology for adults with rare cancers. Statement of SignificanceThis study presents a biopsy-compatible drug sensitivity testing platform for phenotype-based therapy stratification in rare cancers. It identifies actionable ex vivo drug responses and shows associations with clinical outcome in patients treated with screened therapies. These findings support functional testing as a complementary additional layer of stratification for therapeutic prioritization.

cancer biology↗

Post-transcriptional regulation of insulin mRNA storage by G3BP1/2+ condensates in beta cells

Hyperglycemia upregulates insulin translation in pancreatic beta cells. Several RNA- binding proteins involved in this process have been identified, including G3BP1, a stress granule marker downregulated in islets of subjects with type 2 diabetes. We show that in mouse insulinoma MIN6-K8 cells exposed to fasting glucose levels G3BP1 and its paralog G3BP2 colocalize to cytosolic condensates with eIF3b and Ins1/2 mRNA. Upon glucose stimulation, the condensates dissolve and G3BP1/2, eIF3b, and insulin mRNAs redistribute throughout the cytosol. Intriguingly, G3BP1+ condensates in MIN6-K8 cells differ from sodium arsenate-induced stress granules in regards to eIF2 and AMPK phosphorylation. Knockout of G3BP1 or G3BP2 prevented condensate assembly, but only G3BP1 deletion decreased the levels of Ins1/2 mRNA and proinsulin and impaired polysome formation. Like glucose, other insulin secretagogues such as Exendin-4 and palmitate, but not high KCl, prompted the dissolution of G3BP1+ condensates. G3BP1+/Ins mRNA+ condensates were also present in mouse and human beta cells from normoglycemic donors. Hence, G3BP1+ condensates represent a glucose-regulated compartment for the physiological storage and protection of insulin mRNA in resting beta cells.

molecular biology↗

Phage infection fronts trigger early sporulation and collective defense in bacterial populations

I.Bacteriophage (phage) infect, lyse, and propagate within bacterial populations. However, physiological changes in bacterial cell state can protect against infection even within genetically susceptible populations. One such example is the generation of endospores by Bacillus and its relatives, characterized by a reversible state of reduced metabolic activity that protects cells against stressors including desiccation, energy limitation, antibiotics, and infection by phage. Here we tested how sporulation at the cellular scale impacts phage dynamics at population scales when propagating amongst B. subtilis in spatially structured environments. Initially, we found that plaques resulting from infection and lysis were approximately 3-fold smaller on lawns of sporulating wild-type bacteria vs. non-sporulating bacteria. Notably, plaque size was reduced due to an early termination of expanding phage plaques rather than the reduction of plaque growth speed. Microscopic imaging of the plaques revealed sporulation rings, i.e., spores enriched around plaque edges relative to phage-free regions. We developed a series of mathematical models of phage, bacteria, spore, and small molecules that recapitulate plaque dynamics and identify a putative mechanism: sporulation rings arise in response to lytic activity. In aggregate, sporulation rings inhibit phage from accessing susceptible cells even when sufficient resources are available for further infection and lysis. Together, our findings identify how dormancy can self-limit phage infections at population scales, opening new avenues to explore the entangled fates of phages and their bacterial hosts in environmental and therapeutic contexts.

microbiology↗

Design, optimization, and inference of multiphasic decay of infectious virus particles

Virus population dynamics are driven by counter-balancing forces of production and loss. Whereas viral production arises from complex interactions with susceptible hosts, the loss of infectious virus particles is often approximated as a first-order kinetic process. As such, experimental protocols to measure infectious virus loss are not typically designed to identify non-exponential decay processes. Here, we propose methods to evaluate if an experimental design is adequate to identify multiphasic virus particle decay and to optimize the sampling times of decay experiments, accounting for uncertainties in viral kinetics. First, we evaluate synthetic scenarios of biphasic decays, with varying decay rates and initial proportions of subpopulations. We show that robust inference of multiphasic decay is more likely when the faster decaying subpopulation predominates insofar as early samples are taken to resolve the faster decay rate. Moreover, design optimization involving non-equal spacing between observations increases the precision of estimation while reducing the number of samples. We then apply these methods to infer multiple decay rates associated with the decay of bacteriophage ( phage) {Phi}D9, an evolved isolate derived from phage {Phi}21. A pilot experiment confirmed that {Phi}D9 decay is multiphasic, but was unable to resolve the rate or proportion of the fast decaying subpopulation(s). We then applied a Fisher information matrix-based design optimization method to propose nonequally spaced sampling times. Using this strategy, we were able to robustly estimate multiple decay rates and the size of the respective subpopulations. Notably, we conclude that the vast majority (94%) of the phage {Phi}D9 population decays at a rate 16-fold higher than the slow decaying population. Altogether, these results provide both a rationale and a practical approach to quantitatively estimate heterogeneity in viral decay.

microbiology↗

Structure, interaction, and nervous connectivity of beta cell primary cilia

Primary cilia are sensory organelles present in many cell types. Based on an array of microtubules termed axoneme they form a specialized membrane compartment partaking in various signaling processes. Primary cilia of pancreatic islet beta cells play a role in autocrine and paracrine signaling and are linked to diabetes. Yet, the structural basis for their functions is unclear. We present three-dimensional reconstructions of complete mouse and human beta cell cilia, revealing a disorganized 9+0 axoneme structure. Within the islet, cilia are spatially confined within deep ciliary pockets or squeezed into narrow extracellular spaces between adjacent cells. Beta and alpha cell cilia physically interact with neighboring islet cells pushing and strongly bending their plasma membranes. Furthermore, beta cells can contain multiple cilia that can meet with other islet cell cilia in the extracellular space. Additionally, beta cell cilia establish connections with islet-projecting nerves. These findings highlight the pivotal role of beta cell primary cilia in islet cell connectivity, pointing at their potential functional role in integrating islet intrinsic and extrinsic signals. These novel insights contribute to understanding their significance in health and diabetes.

cell biology↗

Coevolution with a seed bank

Dormancy is as an adaptation to living in fluctuating environments. It can also influence species interactions, for example, by providing organisms with a refuge from predators and parasites. Here we test the hypothesis that dormancy generates a seed bank of protected individuals that can modify antagonistic coevolutionary dynamics. We experimentally evolved a spore-forming bacterial host along with a phage parasite that can infect active but not dormant cells. Seed banks buffered population dynamics against phage infection and retained phenotypic diversity that was otherwise lost to directional selection. By storing genetic diversity, seed banks also altered the distribution of host alleles, which contributed to dampened coevolutionary dynamics. Our findings demonstrate that dormancy generates a seed bank that can modify the eco-evolutionary outcomes of host-parasite systems.

evolutionary biology↗

Emergence and maintenance of stable coexistence during a long-term multicellular evolution experiment

The evolution of multicellular life spurred evolutionary radiations, fundamentally changing many of Earths ecosystems. Yet little is known about how early steps in the evolution of multicellularity transform eco-evolutionary dynamics, e.g., via niche expansion processes that may facilitate coexistence. Using long-term experimental evolution in the snowflake yeast model system, we show that the evolution of multicellularity drove niche partitioning and the adaptive divergence of two distinct, specialized lineages from a single multicellular ancestor. Over 715 daily transfers, snowflake yeast were subject to selection for rapid growth in rich media, followed by selection favoring larger group size. Both small and large cluster-forming lineages evolved from a monomorphic ancestor, coexisting for over ~4,300 generations. These small and large sized snowflake yeast lineages specialized on divergent aspects of a trade-off between growth rate and survival, mirroring predictions from ecological theory. Through modeling and experimentation, we demonstrate that coexistence is maintained by a trade-off between organismal size and competitiveness for dissolved oxygen. Taken together, this work shows how the evolution of a new level of biological individuality can rapidly drive adaptive diversification and the expansion of a nascent multicellular niche, one of the most historically-impactful emergent properties of this evolutionary transition.

evolutionary biology↗

Metacommunity Structure Preserves Genome Diversity in the Presence of Gene-specific Selective Sweeps.

The horizontal transfer of genes is fundamental for the eco-evolutionary dynamics of microbial communities, such as oceanic plankton, soil, and the human microbiome. In the case of an acquired beneficial gene, classic population genetics would predict a genome-wide selective sweep, whereby the genome spreads clonally with the gene, removing genome diversity. Instead, several sources of metagenomic data show the existence of "gene-specific sweeps", whereby a beneficial gene spreads across a bacterial community, maintaining genome diversity. Several hypotheses have been proposed to explain this process, including the decreasing gene flow between ecologically distant populations, frequency-dependent selection from linked deleterious allelles, and very high rates of horizontal gene transfer. Here, we propose an additional possible scenario grounded in eco-evolutionary principles. Specifically, we show by a mathematical model and simulations that a metacommunity where species can occupy multiple patches helps maintain genome diversity. Assuming a scenario of patches dominated by single species, our model predicts that diversity only decreases moderately upon the arrival of a new beneficial gene, and that losses in diversity can be quickly restored. We explore the generic behavior of diversity as a function of three key parameters, frequency of insertion of new beneficial genes, migration rates and horizontal transfer rates.Our results provides a testable explanation for how diversity can be maintained given gene-specific sweeps even in the absence of high horizontal gene transfer rates.

evolutionary biology↗

Identification of a unique transcriptomic signature associated with islet amyloidosis

AimsThis cross-sectional study aims to identify potential transcriptomic changes conveyed by presence of amyloid deposits in islets from pancreatic tissue obtained from metabolically profiled living donors. MethodsAfter establishing Thioflavin S as the most sensitive approach to detect islet amyloid plaques, we utilized RNA sequencing data obtained from laser capture microdissected islets to define transcriptomic effects of this pathological entity. The RNA sequencing data was used to identify differentially expressed genes by linear modeling. Further analyses included functional enrichment analysis of KEGG and Hallmark gene sets as well as a weighted gene correlation network analysis. ResultsEleven differentially expressed genes were identified in islets affected by amyloidosis. Enrichment analyses pointed to signatures related to protein aggregation diseases, energy metabolism and inflammatory response. A gene co-expression module was identified that correlated to islet amyloidosis. ConclusionAlthough the influence of underlying Type 2 diabetes could not be entirely excluded, this study presents a valuable insight into the biology of islet amyloidosis, particularly providing hints into the potential relationship between islet amyloid deposition and structural and functional proteins involved in insulin secretion. Research in contextO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LIIslet amyloidosis is the only histological marker of Type 2 diabetes in the pancreas C_LIO_LIIndividuals not suffering from Type 2 diabetes can also be affected by islet amyloidosis C_LIO_LIThe clinicopathological significance of this phenomenon is still unclear C_LI What is the key question?O_LIDoes the islet transcriptome of individuals with islet amyloidosis provide explanations for the onset of this phenomenon and its pathophysiological value? C_LI What are the new findings?O_LIIslet transcriptomes of affected subjects exhibit only limited transcriptomic differences compared to unaffected ones. C_LIO_LIStructural and functional proteins involved in insulin secretion machinery may be involved in the pathophysiological sequence of amyloid formation C_LI

systems biology↗

Optimal dormancy strategies in fluctuating environments given delays in phenotypic switching

Organisms have evolved different mechanisms in response to periods of environmental stress, including dormancy - a reversible state of reduced metabolic activity. Transitions to and from dormancy can be random or induced by changes in environmental conditions. Prior theoretical work has shown that stochastic transitioning between active and dormant states at the individual level can maximize fitness at the population level. However, such theories of bet-hedging strategies typically neglect certain physiological features of transitions to dormancy, including time lags to gain protective benefits. Here, we construct and analyze a dynamic model that couples stochastic changes in environmental state with the population dynamics of organisms that can initiate dormancy after an explicit time delay. Stochastic environments are simulated using a multi-state Markov chain through which the mean and variance of environmental residence time can be adjusted. In the absence of time lags (or in the limit of very short lags), we find that bet-hedging strategy transition probabilities scale inversely with the mean environmental residence times, consistent with prior theory. We also find that increasing delays in dormancy decreases optimal transitioning probabilities, an effect that can be influenced by the correlations of environmental noise. When environmental residence times - either good or bad - are uncorrelated, the maximum population level fitness is obtained given low levels of transitioning between active and dormant states. However when environmental residence times are correlated, optimal dormancy initiation and termination probabilities increase insofar as the mean environmental persistent time is longer than the delay to reach dormancy. We also find that bet hedging is no longer advantageous when delays to enter dormancy exceed the mean environmental residence times. Altogether, these results show how physiological limits to dormancy and environmental dynamics shape the evolutionary benefits and even viability of bet hedging strategies at population scales.

ecology↗

Plasmacytoid dendritic cells regulate megakaryocyte and platelet homeostasis

Platelet homeostasis is essential for vascular integrity and immune defense. While the process of platelet formation by fragmenting megakaryocytes (thrombopoiesis) has been extensively studied, the cellular and molecular mechanisms required to constantly replenish the pool of megakaryocytes by their progenitor cells (megakaryopoiesis) remains unclear. Here we use intravital 2 photon microscopy to track individual megakaryopoiesis over days. We identify plasmacytoid dendritic cells (pDCs) as crucial bone marrow niche cells that regulate megakaryopoiesis. pDCs monitor the bone marrow for platelet-producing megakaryocytes and deliver IFN- to the megakaryocytic niche to trigger local on-demand proliferation of megakaryocyte progenitors. This fine-tuned coordination between thrombopoiesis and megakaryopoiesis is crucial for megakaryocyte and platelet homeostasis in steady state and stress. However, uncontrolled pDC function within the megakaryocytic niche is detrimental. Accordingly, we show that pDCs activated by SARS-CoV2 drive inappropriate megakaryopoiesis associated with thrombotic complications. Together, we uncover a hitherto unknown megakaryocytic bone marrow niche maintained by the constitutive delivery of pDC-derived IFN-.

immunology↗

Germline loss-of-function variants in the base-excision repair gene MBD4 cause a Mendelian recessive syndrome of adenomatous colorectal polyposis and acute myeloid leukaemia

Inherited defects in base-excision repair (BER) predispose to adenomatous polyposis and colorectal cancer (CRC), yet our understanding of this important DNA repair pathway remains incomplete. By combining detailed clinical, histological and molecular profiling, we reveal biallelic germline loss-of-function (LOF) variants in the BER gene MBD4 to predispose to adenomatous polyposis and -uniquely amongst CRC predisposition syndromes- to myeloid neoplasms. Neoplasms from MBD4-deficient patients almost exclusively accumulate somatic CpG>TpG mutations, resembling mutational signature SBS1. MBD4-deficient adenomas harbour mutations in known CRC driver genes, although AMER1 mutations were more common and KRAS mutations less frequent. We did not find an increased risk for colorectal tumours in individuals with a monoallelic MBD4 LOF variant. We suggest that this condition should be termed MBD4-associated neoplasia syndrome (MANS) and that MBD4 is included in testing for the genetic diagnosis of polyposis and/or early-onset AML.

genetics↗

Multi-omics profiling of living human pancreatic islet donors reveals heterogeneous beta cell trajectories toward type 2 diabetes

Existing studies do not sufficiently describe the molecular changes of pancreatic islet beta cells leading to their deficient insulin secretion in type 2 diabetes (T2D). Here we address this deficiency with a comprehensive multi-omics analysis of metabolically profiled pancreatectomized living human donors stratified along the glycemic continuum from normoglycemia to T2D. Islet pools isolated from surgical samples by laser-capture microdissection had remarkably heterogeneous transcriptomic and proteomic profiles in diabetics, but not in non-diabetic controls. Transcriptomics analysis of this unique cohort revealed islet genes already dysregulated in prediabetic individuals with impaired glucose tolerance. Our findings demonstrate a progressive but disharmonic remodeling of mature beta cells, challenging current hypotheses of linear trajectories toward precursor or trans-differentiation stages in T2D. Further, integration of islet transcriptomics and pre-operative blood plasma lipidomics data enabled us to define the relative importance of gene co-expression modules and lipids positively or negatively associated with HbA1c levels, pointing to potential prognostic markers.

bioinformatics↗

Leapfrog dynamics in phage-bacteria coevolution revealed by joint analysis of cross-infection phenotypes and whole genome sequencing

Viruses and their hosts can undergo coevolutionary arms races where hosts evolve increased resistance and viruses evolve counter-resistance. Given these arms race dynamics (ARD), viruses and hosts are each predicted to evolve along a single trajectory as more recently evolved genotypes replace their predecessors. Here, by coupling phenotypic and genomic analyses of coevolving populations of bacteriophage {lambda} and Escherichia coli, we find conflicting evidence for ARD. Virus-host infection phenotypes fit the ARD model, yet whole genome analyses did not. Rather than coevolution unfolding along a single trajectory, cryptic genetic variation emerges during initial virus-host coevolution. This variation is maintained across generations and eventually supplants dominant lineages. These observations constitute what we term leapfrog coevolutionary dynamics, revealing weaknesses in the predictive power of standard coevolutionary models. The findings shed light on the mechanisms that structure coevolving ecological networks and reveal the limits of using phenotypic assays alone in characterizing coevolutionary dynamics.

evolutionary biology↗

A thermal trade-off between viral production and degradation drives phytoplankton-virus population dynamics

Marine viruses interact with their microbial hosts in dynamic environments shaped by variations in abiotic factors, including temperature. However, the impacts of temperature on viral infection of phytoplankton are not well understood. Here we coupled mathematical modeling with experimental datasets to explore the effect of temperature on three Micromonas-prasinovirus pairs. Our model shows the negative consequences of high temperatures on infection and suggests a temperature-dependent threshold between viral production and degradation. Modeling long-term dynamics in environments with different average temperatures revealed the potential for long-term host-virus coexistence, epidemic free, or habitat loss states. Hence, we generalized our model to global sea surface temperature of present and future seas and show that climate change may influence virus-host dynamics differently depending on the virus-host pair. Our study suggests that temperature-dependent changes in the infectivity of virus particles may lead to shifts in virus-host habitats in warmer oceans, analogous to projected changes in the habitats of macro- and micro-organisms.

ecology↗

Optimizing the Timing and Composition of Therapeutic Phage Cocktails: A Control-theoretic Approach

Viruses that infect bacteria, i.e., bacteriophage or phage, are increasingly considered as treatment options for the control and clearance of bacterial infections, particularly as compassionate use therapy for multi-drug resistant infections. In practice, clinical use of phage often involves the application of multiple therapeutic phage, either together or sequentially. However, the selection and timing of therapeutic phage delivery remains largely ad hoc. In this study, we evaluate principles underlying why careful application of multiple phage (i.e., a cocktail) might lead to therapeutic success in contrast to the failure of single-strain phage therapy to control an infection. First, we use a nonlinear dynamics model of within-host interactions to show that a combination of fast intra-host phage decay, evolution of phage resistance amongst bacteria, and/or compromised immune response might limit the effectiveness of single-strain phage therapy. To resolve these problems, we combine dynamical modeling of phage, bacteria, and host immune cell populations with control-theoretic principles (via optimal control theory) to devise evolutionarily robust phage cocktails and delivery schedules to control the bacterial populations. Our numerical results suggest that optimal administration of single-strain phage therapy may be sufficient for curative outcomes in immunocompetent patients, but may fail in immunodeficient hosts due to phage resistance. We show that optimized treatment with a two-phage cocktail that includes a counter-resistant phage can restore therapeutic efficacy in immunodeficient hosts.

microbiology↗

PANCREATIC ISLETS COMMUNICATE WITH THE BRAIN VIA VAGAL SENSORY NEURONS

Depleting visceral sensory nerves affects pancreatic islet function, glucose metabolism and diabetes onset, but how islet endocrine cells interact with sensory neurons has not been studied. Here we show that the pancreatic islet is innervated by vagal sensory axons expressing substance P, calcitonin-gene related peptide, and serotonin receptor 5HT3R. Vagal neurons projecting to the pancreas terminate in the commissural nucleus of the solitary tract. These neurons respond to chemical but not mechanical stimulation of the pancreas. By recording activity from nodose neurons in vivo and from sensory axons in living pancreas slices, we show that sensory nerves respond to serotonin secreted from stimulated beta cells. Serotonin is co-released with insulin and therefore conveys information about the secretory state of beta cells via vagal afferent nerves. Our study thus establishes that pancreatic islets communicate with the brain using the neural route and identifies serotonin signaling as a peripheral transduction mechanism.

neuroscience↗

Linking light-dependent life history traits with population dynamics for Prochlorococcus and cyanophage

Prochlorococcus grow in diurnal rhythms driven by diel cycles. Their ecology depends on light, nutrients, and top-down mortality processes including lysis by viruses. Cyanophage, viruses that infect cyanobacteria, are also impacted by light. For example, extracellular viability and intra-cell infection kinetics of some cyanophage vary between light and dark conditions. Nonetheless, it remains unclear if light-dependent viral life history traits scale-up to influence population-level dynamics. Here we examined the impact of diel-forcing on both cellular- and population-scale dynamics in multiple Prochlorococcus-phage systems. To do so, we developed a light-driven population model including both cellular growth and viral infection dynamics. We then tested the model against measurements of experimental infection dynamics with diel forcing to examine the extent to which population level changes in both viral and host abundances could be explained by light-dependent life history traits. Model-data integration reveals that light-dependent adsorption can improve fits to population dynamics for some virus-host pairs. However, light-dependent variation alone does not fully explain realized host and virus population dynamics. Instead, we show evidence of a previously unrecognized lysis saturation at relatively high virus to cell ratios. Altogether, our study represents a quantitative approach to integrate mechanistic models to reconcile Prochlorococcus-virus dynamics spanning cellular to population scales.

microbiology↗