Biology subjects

Goyal, A.

Publications and source records attributed to Goyal, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Colocalization between bone loading and metabolic activity in the human tibia in response to acute exercise

Bone strain and remodeling are important factors for bone health. Improved characterization of relationships between these factors in response to acute loading will improve our understanding of bone maintenance, adaptation to load, and pathophysiology. The purpose of this study was to evaluate colocalization between finite-element-estimated bone strain and [18F]sodium fluoride positron emission tomography imaging-estimated subchondral bone remodeling in the tibial diaphysis in response to acute exercise. We hypothesized that the exercise-induced change in standardized uptake values would be greatest in regions of higher strain. 26 participants underwent bilateral positron emission tomography/magnetic resonance scans before and after a bout of stair ascent and descent exercise. Finite element analysis was performed to calculate principal strain distributions in the tibial diaphysis. [18F]sodium fluoride standardized uptake values were calculated from pre- and post-exercise positron emission tomography data and mapped to the tibial surface. Mean pre-exercise and exercise-induced change in standardized uptake values were calculated and compared between regions defined by strain percentile. Both normalized mean pre-exercise and exercise-induced change in standardized uptake values increased with maximum principal strain in a pattern suggesting an exponential relationship. Pre-exercise and exercise-induced change in standardized uptake value were notably much greater in the region of highest maximum principal strains (estimated marginal means = 76.9 and 71.0 percentile, respectively) when compared to all other regions of the tibial diaphysis ([≤] 61.1 and [≤] 57.0 percentile, respectively, p < 0.001). This study is the first to directly show a relationship between bone mechanical loads and acute [18F]sodium fluoride uptake in humans in vivo. Our results highlight the influence of tensile strain magnitude on bone metabolic activity in response to acute loading. Furthermore, we demonstrate the utility of a combined finite element analysis and positron emission tomography approach to interrogate relationships between bone loading and bone metabolic response to acute exercise.

bioengineering↗

bioRxiv2026

Environmental history can counteract nutrient quality in shaping the evolution of bacterial growth rates

Despite sharing nearly identical enzymes, strains of the same microbial species display wide variability of growth rates when growing on the same nutrients. Here, we show that such growth rate variability can emerge as a consequence of evolutionary adaptation to different patterns of environmental fluctuations. We develop a mathematical model combining cellular proteome allocation with eco-evolutionary dynamics in fluctuating environments. We find that different patterns of environmental fluctuations select for distinct growth profiles. Slow-growing strains repeatedly outcompete fast-growers when evolved in rapidly changing environments. In a range of environments with asymmetric nutrient availability, evolution reproducibly leads to the robust diversification of two coexisting strains. We develop a theoretical framework based on adaptive dynamics which quantitatively predicts these evolutionary outcomes and explains them in terms of the growth-lag tradeoff that all cells face. Finally, we show that the model can reproduce several patterns in growth-rate data from closely-related strains. Our results highlight that bacterial growth rates can rapidly adapt to their recent environmental history by proteome allocation alone, in ways that often oppose expectations based on nutrient quality.

evolutionary biology↗

bioRxiv2026

Resource supply dynamics control stability and chaos in complex ecosystems

Ecological interactions are often mediated by feedbacks between organisms and their resource environments. Yet, how resource supply dynamics dictate collective dynamical phases of an ecosystem remains unclear. Here, we analyse a generalised consumer--resource model with non-reciprocal interactions to demonstrate that self-renewing versus externally-supplied resources yield fundamentally different dynamical phase diagrams. As interactions become increasingly non-reciprocal, ecosystems relying on self-renewing resources transition from stable dynamics to chaos and ultimately to infeasibility. By contrast, ecosystems with externally-supplied resources remain stable over a broader parameter range and transition to infeasibility without experiencing an intervening chaotic phase. Using the cavity method, we derive a unified stability condition applicable to a broad class of resource supply functions, explaining why externally-supplied resources can expand the stable region. We show that stability hinges crucially on the susceptibility of resources to perturbations, which depends strongly on their supply. Further, we show that external resource supply suppresses chaos in the unstable region by drastically reducing the susceptibility of resources closest to extinction. Our findings demonstrate that resource dynamics fundamentally reshape the accessible dynamical behaviours of an ecosystem, with implications for interpreting microbial community experiments.

ecology↗

bioRxiv2026

Nutrient availability shapes the diversity and structure ofmicrobial communities

Nutrients are key drivers of microbial community structure, yet we lack a data-driven quantitative framework linking nutrient environments to community assembly. Here, using controlled microcosm experiments, we systematically probe the effects of nutrient number, concentration, and type on community diversity and structure. To explain these effects, we construct a minimal consumer-resource model incorporating resource competition and cross-feeding. We find that cross-feeding network structure is critical: only shallow, wide networks -- where several byproducts are produced from a few supplied nutrients in a few trophic layers -- reproduce a linear increase in diversity with the number of supplied nutrients. We also perform new experiments varying nutrient concentration and reveal that diversity slowly decreases with increasing concentration. We explain this finding by incorporating consumption-dependent toxicity into the model, consistent with spent-media measurements. This extended model not only recapitulates virtually all observed patterns but makes an independent prediction: at high nutrient concentrations, communities should be enriched in bistable species pairs, which we confirm experimentally. Our work demonstrates that minimal data-driven consumer-resource frameworks -- systematically constrained by experiments -- can unify and predict a broad range of nutrient-community relationships.

ecology↗

bioRxiv2026

Emergent frequency-dependent selection predicts mutation outcomes in complex ecological communities

Ecological interactions can dramatically alter evolutionary outcomes in complex communities. Yet, the framework of population genetics largely neglects interactions from a species-rich community. Here, we bridge this gap by using dynamical mean-field theory to integrate community ecology into classical population genetics models. We show that ecological interactions result in emergent frequency-dependent selection between parents and mutants, characterized by a single parameter measuring the strength of ecological feedbacks. This result generalizes classical population genetics models to highly diverse communities and enables predictions of mutation outcomes in these eco-evolutionary settings. We derive an analytic expression for fixation probability that extends Kimuras formula and reveals that ecological interactions strongly suppress the fixation of moderately beneficial mutations. This suppression arises because frequency-dependent selection leads to prolonged coexistence between parent and mutant lineages, which acts as a barrier to fixation. The strength of these effects increases with effective population size and the number of open niches in the ecosystem. Our study establishes a framework for integrating ecological interactions into population genetics, showing that evolutionary outcomes can be predicted using simple models even in the presence of complex community feedbacks.

evolutionary biology↗

bioRxiv2026

Diverse communities promote the coexistence of closely-related strains through emergent equalization and stabilization

Microbial communities harbor extensive fine-scale diversity: closely-related strains of the same species coexist alongside many distantly-related taxa. Yet strain coexistence remains poorly understood, largely because most studies neglect the diverse communities in which strains are embedded. Here we combine community ecology and statistical physics to study the dynamics of closely-related strains in a community context. We demonstrate that in a diverse community, indirect interactions between strains--mediated through the surrounding community members--can be as strong as direct ones. These community-mediated feedbacks cause conspecific strains to behave as if they have correlated growth rates and reduced competition. Using modern coexistence theory, we show that these effects correspond to equalizing and stabilizing mechanisms which together promote strain coexistence. The same equalizing and stabilizing mechanisms also qualitatively transform strain abundance correlations: strains that compete strongly and show negative correlations in isolation instead show positive correlations in a community, appearing mutualistic despite being competitors. Our results demonstrate that strain dynamics are emergent consequences of the surrounding community, and that capturing community feedbacks does not require the full interaction network; only a small number of emergent parameters.

ecology↗

bioRxiv2026

Api5-FGF2 regulates the transformation of breast epithelial cells via PDK1/Akt and Ras/MAPK/ERK signalling

The equilibrium between cell death and cell division is crucial for maintaining tissue homeostasis in a multicellular organism. Apoptosis plays an essential role in preserving homeostasis and hence occurs in a coordinated manner. However, inhibition of apoptosis is one of the hallmarks of cancer. Apoptosis Inhibitor 5 (Api5), an anti-apoptotic protein, is upregulated in various cancers, including ovarian, bladder, cervical, and lung cancers. Studies have demonstrated that altered expression of Api5 leads to the transformation of non-tumorigenic breast epithelial cells. However, the mechanism regulating this process is not well-elucidated. Our study demonstrates that overexpression of Api5 increased FGF2 (Fibroblast Growth Factor 2) levels both at protein and transcript levels. We studied the mechanistic details of changes in morphology, proliferation, and polarity observed upon FGF2/FGFR1 deregulation in Api5-overexpressing cells. Deciphering the signalling mechanism underlying Api5-FGF2-mediated breast tumorigenesis revealed that the PDK1/Akt and Ras/MAPK/ERK pathways regulated multiple transformation phenotypes. PDK1/Akt enhanced proliferation and altered morphology during initial stages, whereas Ras/MAPK/ERK regulated polarity disruption, proliferation, and reduced apoptosis during later stages of morphogenesis. In conclusion, this study provides insights into the signalling mechanism regulating the transformation phenotypes associated with Api5 overexpression in a non-tumorigenic breast epithelial cell line.

cancer biology↗

bioRxiv2026

Energy flow controls the stability of multitrophic ecosystems with stratified nonreciprocity

Complex systems with nonreciprocal interactions are often stratified into layers. Ecosystems are a prime example, where species at one trophic level grow by consuming those at another. Yet the dynamical consequences of such stratified nonreciprocity--where the correlation between growth and consumption differs across trophic levels--remain unexplored. Here, using an ecological model with three trophic levels, we reveal an emergent asymmetry: nonreciprocal interactions between consumers and predators (top and middle level) destabilize ecosystems far more readily than non-reciprocity between consumers and resources (middle and bottom level). We analytically derive the phase diagram for the model and show that its stability boundary is controlled by energy flow across trophic levels. Because energy flows upward--from resources to predators--diversity is progressively lower at higher trophic levels, which we show explains the asymmetry. Lowering energy flow efficiency flips the asymmetry toward resources and remarkably expands the stable region of the phase diagram, suggesting that the famous "10% energy transfer" seen in natural ecosystems might promote stability. More broadly, our findings show that the location of nonreciprocity within a complex network, not merely its magnitude, determines stability.

ecology↗

bioRxiv2025

Resource ratio fluctuations drive the evolution of microbial metabolic strategies

Microorganisms employ diverse metabolic strategies to cope with environmental variability, yet the evolutionary conditions that favor specialists, hierarchical utilizers, or co-utilizers remain poorly understood. Here, we investigate how fluctuations in resource supply ratios drive the evolution of metabolic strategies. By simulating microbial community assembly in environments with variable resource ratios, we show that diverse metabolic strategies emerge as evolutionary optima in different fluctuation regimes. We find that environments with balanced resource supply select for specialists, whereas imbalanced environments select for generalists. As the magnitude of fluctuations in resource supply ratios progressively increases, generalist strategies smoothly shift from those of hierarchical utilizers to co-utilizers. We identify the duration of temporal niches as the mechanistic driver that selects for reduced lag times over maximal growth rates. These findings demonstrate how the temporal structure of resource availability can spontaneously generate the three distinct metabolic strategies observed in nature.

ecology↗

bioRxiv2025

Emergent self-inhibition governs the landscape of stable states in complex ecosystems

Species-rich ecosystems often exhibit multiple stable states with distinct species compositions. Yet, the factors determining the likelihood of each states occurrence remain poorly understood. Here, we characterize and explain the landscape of stable states in the random Generalized Lotka-Volterra (GLV) model, in which multistability is widespread. We find that the same pool of species with random initial abundances can result in different stable states, whose likelihoods typically differ by orders of magnitude. A states likelihood increases sharply with its total biomass, or inverse self-inhibition. We develop a simplified model to predict and explain this behavior, by coarse-graining ecological interactions so that each stable state behaves as a unit. In this setting, we can accurately predict the entire landscape of stable states using only two macroscopic properties: the biomass of each state and species diversity. Our analyses also provide insight into the biomass-likelihood relationship: High-biomass states have low self-inhibition and thus grow faster, outcompete others, and become much more likely. These results reveal emergent self-inhibition as a fundamental organizing principle for the attractor landscape of complex ecosystems--and provide a path to predict ecosystem outcomes without knowing microscopic interactions.

ecology↗

bioRxiv2025

Resource diversity begets stability in complex ecosystems

A fundamental paradox in ecology is the relationship between species diversity and ecosystem stability: Mays stability condition predicts that species diversity destabilises communities, yet many diverse ecosystems in nature are stable. Here, we show that this paradox can be resolved by explicitly considering resources, which May neglects. Specifically, Mays framework and the competitive exclusion principle jointly predict that resource diversity, which promotes species diversity, should destabilise communities. However, from computer simulations and analytical calculations using the finite-size cavity method, we find the opposite: resource diversity consistently generates stable, species-rich communities. Importantly, this stabilising effect disappears when resource dynamics is neglected (set to steady state). We also show that, contrary to the prevailing belief that interaction heterogeneity is always destabilising, different biological sources of heterogeneity have opposing effects on stability. Our work provides a solution to Mays paradox and demonstrates that resource dynamics are not just negligible background but are central drivers of ecosystem stability.

ecology↗

bioRxiv2025

A division of labor controls the degradation of fucoidans in the ocean

Fucoidans--complex polysaccharides produced by brown algae and diatoms--contribute to long-term carbon sequestration due to their resistance to microbial degradation1,2. While individual microbes can break down portions of these polymers3-5, it remains unclear whether complete breakdown is possible in nature and, if so, by what mechanisms. Here we show that fucoidans are degraded through synergistic interactions between specialized bacteria with conserved metabolic functions. Using metabolomic analysis of a reconstructed marine consortium, we uncovered functional guilds of bacteria that target either the sulfated fucose backbone or the side-branches of rare monomers. This division of labor leads to an unexpectedly high number of positive interactions between different degraders that enhanced degradation efficiency up to 97.1%. Despite variation in fucoidan structure across different types of algae, the metabolic functions of degraders remained conserved, enabling quantitative prediction of degradation outcomes based on community composition. Our findings suggest that the environmental turnover of complex macromolecules depends not only on individual metabolic capabilities but also on ecological interactions shaped by substrate architecture. This work provides a mechanistic framework for understanding carbon cycling in the ocean and for engineering synthetic microbial consortia to degrade recalcitrant polysaccharides.

microbiology↗

bioRxiv2025

Ecosystems as adaptive living circuits

Unlike many physical nonequilibrium systems, in biological systems, the coupling to external energy sources is not a fixed parameter but adaptively controlled by the system itself. We do not have theoretical frameworks that allow for such adaptability. As a result, we cannot understand emergent behavior in living systems where structure formation and non-equilibrium drive coevolve. Here, using ecosystems as a model of adaptive systems, we develop a framework of living circuits whose architecture changes adaptively with the energy dissipated in each circuit edge. We find that unlike traditional nonequilibrium systems, living circuits exhibit a phase transition from equilibrium death to a nonequilibrium dissipative state beyond a critical driving potential. This transition emerges through a feedback mechanism that saves the weakest edges by routing dissipation through them, even though the adaptive rule locally rewards the strongest dissipating edges. Despite lacking any global optimization principle, living circuits achieve near-maximal dissipation, with higher drive promoting more complex circuits. Our work establishes ecosystems as paradigmatic examples of living circuits whose structure and dissipation are tuned through local adaptive rules.

ecology↗

bioRxiv2025

Structured interactions explain the absence of keystone species in synthetic microcosms

In complex ecosystems, the loss of certain species can trigger a cascade of secondary extinctions and invasions. However, our understanding of the prevalence of these critical "keystone" species and the factors influencing their emergence remains limited. To address these questions, we experimentally assembled microcosms from 16 marine bacterial species and found that multiple extinctions and invasions were exceedingly rare upon removal of a species from the initial inoculation. This was true across eight different environments with either simple carbon sources (e.g., glucose) and more complex ones (e.g. glycogen). By employing a generalized Lotka-Volterra model, we could reproduce these results when interspecies interactions followed a hierarchical pattern, wherein species impacted strongly by one species were also more likely to experience strong impacts from others. Such a pattern naturally emerges due to observed variation in carrying capacities and growth rates. Furthermore, using both statistical inference and spent media experiments, we inferred interspecies interaction strengths and found them consistent with structured interactions. Our results suggest that the natural emergence of structured interactions may provide community resilience to extinctions.

systems biology↗

bioRxiv2025

A theory of ecological invasions and its implications for eco-evolutionary dynamics

Predicting the outcomes of species invasions is a central goal of ecology, a task made especially challenging due to ecological feedbacks. To address this, we develop a general theory of ecological invasions applicable to a wide variety of ecological models: including Lotka-Volterra models, consumer resource models, and models with cross feeding. Importantly, our framework remains valid even when invading evolved (non-random) communities and accounts for invasion-driven species extinctions. We derive analytical expressions relating invasion fitness to invader abundance, shifts in the community, and extinction probabilities. These results can be understood through a new quantity we term "dressed invasion fitness", which augments the traditional notion of invasion fitness by incorporating ecological feedbacks. We apply our theory to analyze short-term evolutionary dynamics through a series of invasions by mutants whose traits are correlated with an existing parent. We demonstrate that, generically, mutants and parents can coexist, often by driving the extinction of low-abundance species. We validate theoretical predictions against experimental datasets spanning ecosystems from plants to microbial protists. Our work highlights the central role of ecological feedbacks in shaping community responses to invasions and mutations, suggesting that parent-mutant coexistence is widespread in eco-evolutionary dynamics.

ecology↗

bioRxiv2025

A tumor necrosis factor-α responsive cryptic promoter drives overexpression of the human endogenous retrovirus ERVK-7

Endogenous retroviruses (ERVs) shape human genome functionality and influence disease pathogenesis, including cancer. ERVK-7, a significant ERV, acts as an immune modulator and prognostic marker in lung adenocarcinoma (LUAD). Although ERVK-7 overexpression has been linked to the amplification of the 1q22 locus in approximately 10% of LUAD cases, it predominantly arises from alternative regulatory mechanisms. Our findings indicate that the canonical 5 long terminal repeat (LTR) of ERVK-7 is methylated and inactive, necessitating the use of alternative upstream promoters. We identified two novel transcripts, ERVK-7.long and ERVK-7.short, arising from distinct promoters located 2.8 kb and 13.8 kb upstream of the 5LTR of ERVK-7, respectively. ERVK-7.long is predominantly overexpressed in LUAD. Through comprehensive epigenetic mapping and single-cell transcriptomics, we demonstrate that ERVK-7.long activation is predetermined by cell lineage, specifically in small airway epithelial cells (SAECs), where its promoter displays tumor-specific H3K4me3 modifications. Single-cell RNA sequencing further reveals a distinct enrichment of ERVK-7.long in LUAD tumor cells and alveolar type 2 epithelial cells, underscoring a cell-type-specific origin. Additionally, inflammatory signaling significantly influences ERVK-7 expression; TNF- enhances ERVK-7.long, while interferon signaling preferentially augments ERVK-7.short by differential recruitment of NF-{kappa}B/RELA and IRF to their respective promoters. This differential regulation clarifies the elevated ERVK-7 expression in LUAD compared to lung squamous cell carcinoma (LUSC). Our study elucidates the complex regulatory mechanisms governing ERVK-7 in LUAD and proposes these transcripts as potential biomarkers and therapeutic targets, offering new avenues to improve patient outcomes.

cancer biology↗

bioRxiv2024

Estrogens increase cancer cell efferocytosis to establish an immunosuppressive tumor microenvironment

Phagocytic clearance of apoptotic cancer cells (efferocytosis) by tumor-associated macrophages (TAMs) contributes in a substantial manner to the establishment of an immunosuppressive tumor microenvironment. This puts in context our observation that the female steroid hormone 17{beta}- estradiol (E2) facilitates tumor immune resistance through cancer cell extrinsic Estrogen Receptor (ER) signaling in TAMs. Notable was the finding that E2 induces the expression of CX3CR1 in TAMs to enable efferocytosis of apoptotic cancer cells which results in the suppression of type I interferon (IFN) signaling. Mechanistically, E2 facilitates calcium-dependent activation of the transcription factor NFATC1, which in turn induces CX3CR1 expression. This drives macrophage polarization towards an immune-suppressive state, increasing the ability of TAMs to engulf pro- inflammatory apoptotic cancer cells. Genetic or pharmacological inhibition of the E2/ER/CX3CR1 axis reversed the efferocytic activity of TAMs, rescued E2-dependent suppression of type I IFN signaling, and potentiated intratumoral adaptive immune cell function. Efferocytosis following radiation-induced cancer cell apoptosis limits the efficacy of radiation therapy. Importantly, we determined that preconditioning with either ER-directed endocrine therapies or CX3CR1 inhibition enhanced the antitumor efficacy of radiation therapy by reversing macrophage suppression and reviving intratumoral T cell activation. Our work defines the mechanisms by which E2 increases the efferocytotic activity of TAMs to establish an immunosuppressive tumor microenvironment and demonstrates how this process can be reversed with endocrine therapies which target ER.

cancer biology↗

bioRxiv2024

Pyjacker identifies enhancer hijacking events in acute myeloid leukemia including MNX1 activation via deletion 7q

Acute myeloid leukemia with complex karyotype (ckAML) is characterized by high genomic complexity, including frequent TP53 mutations and chromothripsis. We hypothesized that the numerous genomic rearrangements could reposition active enhancers near proto-oncogenes, leading to their aberrant expression. We developed pyjacker, a computational tool for the detection of enhancer hijacking events, and applied it to a cohort of 39 ckAML samples. Pyjacker identified motor neuron and pancreas homeobox 1 (MNX1), a gene aberrantly expressed in 1.4% of AML patients, often as a result of del(7)(q22q36) associated with hijacking of a CDK6 enhancer. MNX1-activated cases show significant co-occurrence with BCOR mutations and a gene signature shared with t(7;12)(q36;p13) pediatric AML. We demonstrated that MNX1 is a dependency gene, as its knockdown in a xenograft model reduces leukemia cell fitness. In conclusion, enhancer hijacking is a frequent mechanism for oncogene activation in AML. Statement of significanceThis study examines the consequences of structural alterations and demonstrates that proto-oncogene activation by enhancer hijacking is an overlooked pathomechanism in AML. MNX1 overexpression demonstrates that deletions on chromosome 7q can not only lead to haploinsufficiency, but also to activation of oncogenes by enhancer hijacking, providing a novel leukemogenic mechanism.

cancer biology↗