Biology subjects

Goldberg, A.

Publications and source records attributed to Goldberg, A..

At least 19 recordsLinked to original sources

bioRxiv2026

What abundance correlations actually measure in stochastic ecological communities

Abundance correlations cannot reveal ecological interactions without an assumption about the covariance of environmental noise. A natural biological expectation is that similar species respond similarly to environmental fluctuations, generating positive correlations. Yet the same species also tend to overlap more strongly in resource use and therefore compete more intensely, generating negative correlations. The simplest plausible benchmark is thus to take environmental-response correlations proportional to niche overlap. We show that, under this assumption and across a broad class of stochastic community models, the two effects cancel exactly: equal-time abundance correlations vanish, independently of interaction strength, heterogeneity, and system size. Away from this matched point, the observed correlations measure primarily the mismatch between shared environmental response and competition, rather than the interaction matrix itself. Correlations can recover information about niche overlap when competitive feedback is delayed relative to environmental forcing, but the inference then depends on a resource-response timescale that is generally not determined by the abundance time series alone. When stochasticity enters through the mechanism that generates similarity itself--for example, through fluctuating shared resources--nonzero correlations may persist, but they reflect yield-depletion mismatch rather than niche overlap. Abundance correlations therefore report how environmental variability reaches the community at least as much as they report who competes with whom.

ecology↗

bioRxiv2026

ZATELLITE: a toolkit to visualize and manipulate human centromeres in live cells using synthetic zinc fingers

Changes in the number of chromosomes or their spatial organization within the nucleus have critical consequences for cell fate. Yet capturing the karyotype or three-dimensional architecture of chromatin in living cells remains limited by the difficulty in labeling endogenous loci non-invasively. The most widely used tools rely on dCas9, a bulky protein whose persistent DNA binding interferes with DNA and RNA metabolism, causes DNA damage, and is hard to multiplex. We developed ZATELLITE, an AI-enabled tool to target endogenous repetitive sequences with fluorescently-tagged synthetic zinc fingers. ZATELLITE probes have key advantages over dCas9: they are smaller, easier to multiplex and, critically, they do not cause DNA damage or chromosomal abnormalities, even after long-term labeling. We generated a collection of ZATELLITE probes to label the centromeres of nearly all human chromosomes, enabling the capture of genome organization and karyotype alterations in real time in living cells. Finally, we show that ZATELLITE can be used for simultaneous labeling and epigenetic editing of centromeres. Thus, ZATELLITE is a non-toxic, versatile tool for genome visualization and manipulation.

cell biology↗

bioRxiv2026

Rare variation in malaria parasites biases population-genetic inference

Understanding how pathogens evolve is fundamental to disease control and is a basic question in evolutionary biology, yet pathogens with complex life cycles violate assumptions of classic evolutionary models. Genetic analyses of the malaria parasite Plasmodium falciparum have shown multiple surprising patterns. For example, empirical analyses produce effective population size estimates that vary by orders of magnitude depending on the method and an excess of genes with elevated nonsynonymous variation (measured as{pi} N /{pi}S). Here, reanalyzing genomic data from 18 worldwide populations, I show that these observations directly follow from distributions of genetic variation enriched for rare variants. Multiple potential mechanisms may increase the proportion of rare variants, including host expansions, lifecycle dynamics, population structure, or selection. The observed genealogies are more consistent with a multiple-merger coalescent than a Kingman coalescent, causing common summary statistics to be biased in predictable directions. In particular, the abundance of rare variants interacts with the mathematical properties of ratio statistics to systematically inflate gene-level{pi} N /{pi}S estimates even in the absence of selection. Notably, filtering this rare variation reveals previously masked candidates for selection, including well-characterized antigens such as merozoite surface proteins. This framework provides a foundation for interpreting genomic data in pathogens with high variance in reproductive success. Significance StatementPathogen genomics increasingly guides public health decisions, yet organisms with complex life cycles can produce genealogies that violate assumptions of standard population genetic methods. Here I show that the malaria parasite Plasmodium falciparum has an excess of rare variation, perhaps produced from overdispersed distributions of reproductive success. These genealogies generate systematic biases in commonly reported statistics arising from the interaction between rare variation and the mathematical properties of the statistics themselves, not from biological processes often invoked to explain anomalous patterns. Correcting for this bias reveals signatures of selection in well-characterized vaccine candidates that were previously masked, demonstrating that appropriate null models are essential for identifying targets of intervention and inferring evolutionary history in pathogens and other systems with reproductive skew.

evolutionary biology↗

bioRxiv2025

Multiple Allosteric Sites Allow for Synergistic Enhancement of GPCR Signaling

Allosteric modulation of G protein-coupled receptors (GPCRs) is an emerging therapeutic paradigm that has proven effective, yet the cooperative action of multiple modulators remains unexplored. Here, we reveal how positive allosteric modulators (PAMs) synergistically enable extraordinary signal amplification through the D1 dopamine receptor (D1R). We developed UNC9815 and UNC10062 as enhanced D1R PAMs from the parent compound MLS6585, and then employed cryo-electron microscopy to reveal concurrent occupancy of three distinct allosteric sites by PAMs of different scaffolds, including LY3154207, BMS-A1, and our UNC compounds. Remarkably, we discovered two adjacent allosteric pockets at the transmembrane helix (TM) 1-7 interface: BMS-A1 occupies an intracellular site promoting activation through TM7 conformational shifts, while the UNC compounds complementarily stabilize the extracellular side of the interface. When combined with LY3154207, this cooperative architecture enhances dopamine potency by more than 1,000-fold. These findings elucidate the first structural blueprint for multi-site GPCR cooperativity, unlocking transformative therapeutic strategies inaccessible to orthosteric and single- site allosteric drugs.

molecular biology↗

bioRxiv2025

Niche Overlap Is Not Enough: Same Overlap, Opposite Dynamics

Niche overlap (NO) is a central concept in coexistence theory, determining the outcome of competitive interactions at equilibrium. Yet, NO is a composite quantity that collapses multiple mechanisms and thus cannot by itself capture community dynamics. We quantify this gap by analyzing one of the simplest out-of-equilibrium observables: temporal correlations in species abundances, widely used in microbial ecology. Within a generalized consumer-resource framework, we separate the mechanistic traits that shape dynamical responses and show that systems with identical NO can display opposite correlation patterns. The decisive predictor is the yield-depletion mismatch (YDM) - the mismatch between species depletion and yield dissimilarities. Analytical theory, stochastic simulations, and a reanalysis of microbial time-series consistently show that YDM, not NO, sets the sign and magnitude of abundance correlations, whereas instantaneous growth-rate correlations increase with NO. Our results suggest that other out-of-equilibrium properties, such as invasion probabilities and coexistence robustness, will likewise be largely independent of NO and instead controlled by distinct out-of-niche parameters.

ecology↗

bioRxiv2025

Activation Mechanism and Structural Assembly of the Mycobacterium tuberculosis ClpP1P2 Protease and Its Associated ATPases.

Supramolecular assemblies are integral to cellular biochemical processes, relying on their dynamic nature to fulfill essential functions. The protease ClpP1P2, paired with ATPase partners ClpC1 or ClpX, is vital for the survival of Mycobacterium tuberculosis (Mtb). While the ClpP1P2 complex requires activation by specific N-blocked dipeptides (e.g., Z-Leu-Leu) to exhibit proteolytic activity in vitro, the mechanism of in vivo activation remains unclear. In this study, we identified novel activators that enabled the structural determination of the ClpC1P1P2 complex, providing insights into its assembly. Furthermore, we discovered that trehalose - a key metabolite and molecular crowding agent in Mtb, significantly enhances the activity of both ClpC1P1P2 and ClpXP1P2 complexes without the need for activating peptides. Analytical ultracentrifugation revealed that trehalose promotes the formation of these active complexes, mimicking intracellular conditions. These findings propose a new model of Clp system activation in vivo, offering promising avenues for therapeutic targeting in tuberculosis treatment. Significance StatementThe proteolytic complex formed by the essential proteins ClpP1 and ClpP2, along with their specific ATP-dependent activators ClpX and ClpC1, has emerged as a highly attractive target for anti-tuberculosis drug development. While previous studies have shown that ClpP1P2 can be activated in vitro by small peptide activators, its in vivo activation mechanism remains unclear. In this study, we identify novel activators and demonstrate that trehalose, a key metabolite in Mycobacterium tuberculosis, enhances ClpC1P1P2 and ClpXP1P2 activity without the need for activating peptides. These findings propose a new model for Clp system activation in Mycobacterium tuberculosis, advancing our understanding of its regulation and potential as a therapeutic target.

biochemistry↗

bioRxiv2024

Rare-Event Sampling using a Reinforcement Learning-Based Weighted Ensemble Method

Despite the power of path sampling strategies in enabling simulations of rare events, such strategies have not reached their full potential. A common challenge that remains is the identification of a progress coordinate that captures the slow relevant motions of a rare event. Here we have developed a weighted ensemble (WE) path sampling strategy that exploits reinforcement learning to automatically identify an effective progress coordinate among a set of potential coordinates during a simulation. We apply our WE strategy with reinforcement learning to three benchmark systems: (i) an egg carton-shaped toy potential, (ii) an S-shaped toy potential, and (iii) a dimer of the HIV-1 capsid protein (C-terminal domain). To enable rapid testing of the latter system at the atomic level, we employed discrete-state synthetic molecular dynamics trajectories using a generative, fine-grained Markov state model that was based on extensive conventional simulations. Our results demonstrate that using concepts from reinforcement learning with a weighted ensemble of trajectories automatically identifies relevant progress coordinates among multiple candidates at a given time during a simulation. Due to the rigorous weighting of trajectories, the simulations maintain rigorous kinetics.

biophysics↗

bioRxiv2024

Differentiating mechanism from outcome for ancestry-assortative mating in admixed human populations

Population genetic theory, and the empirical methods built upon it, often assume that individuals pair randomly for reproduction. However, natural populations frequently violate this assumption, which may potentially confound genome-wide association studies, selection scans, and demographic inference. Within several recently admixed human populations, empirical genetic studies have reported a correlation in global ancestry proportion between spouses, referred to as ancestry-assortative mating. Here, we use forward genomic simulations to link correlations in global ancestry proportion between mates to the underlying mechanistic mate-choice process. We consider the impacts of two types of mate-choice model, using either ancestry-based preferences or social groups as the basis for mate pairing. We find that multiple mate-choice models can produce the same correlations in global ancestry proportion between spouses; however, we also highlight alternative analytic approaches and circumstances in which these models may be distinguished. With this work, we seek to highlight potential pitfalls when interpreting correlations in empirical data as evidence for a particular model of human mating practices, as well as to offer suggestions toward development of new best practices for analysis of human ancestry-assortative mating.

genetics↗

bioRxiv2024

Strategies for motion- and respiration-robust estimation of fMRI intrinsic neural timescales

Intrinsic neural timescale (INT) is a resting-state fMRI (rs-fMRI) measure that reflects the time window of neural integration within a brain region. Despite the potential relevance of INT to cognition, brain organization, and neuropsychiatric illness, the influences of physiological artifacts on INT have not been systematically considered. Two artifacts, head motion and respiration, pose serious issues in rs-fMRI studies. Here, we described their impact on INT estimation and tested the ability of two denoising strategies for mitigating these artifacts, high-motion frame censoring and global signal regression (GSR). We used a subset of the HCP Young Adult dataset with runs annotated for breathing patterns (Lynch et al., 2020) and at least one "clean" (reference) run that had minimal head motion and no respiration artifacts; other runs from the same participants (n = 46) were labeled as "non-clean." We found that non-clean runs exhibited brain-wide increases in INT compared to their respective clean runs and the magnitude of error in INT between non-clean and clean runs correlated with the amount of head motion. Importantly, effect sizes were comparable to INT effects reported in the clinical literature. GSR and high-motion frame censoring improved the similarity between INT maps from non-clean runs and their respective clean run. Using a pseudo-random frame-censoring approach, there was a relationship between the amount of censored frames and both the mean INT and mean error, suggesting that frame censoring itself biases INT estimation. A group-level correction procedure reduced this bias and improved similarity between non-clean runs and their respective clean run. Based on our findings, we offer recommendations for rs-fMRI INT studies, which include implementing GSR and high-motion frame censoring with Lomb-Scargle interpolation of censored data, and performing group-level correction of the bias introduced by frame censoring.

neuroscience↗

bioRxiv2023

The molecular mechanism of positive allosteric modulation at the dopamine D1 receptor

The dopamine D1 receptor (D1R) is a promising target for treating various psychiatric disorders. While upregulation of D1R activity has shown potential in alleviating motor and cognitive symptoms, orthosteric agonists have limitations, restricting their clinical applications. However, the discovery of several allosteric compounds specifically targeting the D1R, such as LY3154207, has opened new therapeutic avenues. Based on the cryo-EM structures of the D1R, we conducted molecular dynamics simulations to investigate the binding and allosteric mechanisms of LY3154207. Our simulations revealed that LY3154207 preferred the horizontal orientation above intracellular loop 2 (IL2) and stabilized the helical conformation of IL2. Moreover, LY3154207 binding induced subtle yet significant changes in key structural motifs and their neighboring residues. Notably, a cluster of residues centered around the Na+ binding site became more compact, while interactions involving the PIF motif and its neighboring residues were loosened upon LY3154207 binding, consistent with their role in opening the intracellular crevice for receptor activation. Additionally, we identified an allosteric pathway likely responsible for the positive allosteric effect of LY3154207 in enhancing Gs protein coupling. This mechanistic understanding of LY3154207s allosteric action at the D1R pave the way for the rational design of more potent and effective allosteric modulators.

biophysics↗

bioRxiv2023

HUWE1 Amplifies Ubiquitin Modifications to Broadly Stimulate Clearance of Proteins and Aggregates

Selective breakdown of proteins and aggregates is crucial for maintaining normal cellular activities and is involved in the pathogenesis of diverse diseases. How the cell recognizes and tags these targets in different structural states for degradation by the proteasome and autophagy pathways has not been well understood. Here, we discovered that a HECT-family ubiquitin ligase HUWE1 is broadly required for the efficient degradation of soluble factors and for the clearance of protein aggregates/condensates. Underlying this capacity of HUWE1 is a novel Ubiquitin-Directed ubiquitin Ligase (UDL) activity which recognizes both soluble substrates and aggregates that carry a high density of ubiquitin chains and rapidly expand the ubiquitin modifications on these targets. Ubiquitin signal amplification by HUWE1 recruits the ubiquitin-dependent segregase p97/VCP to process these targets for subsequent degradation or clearance. HUWE1 controls the cytotoxicity of protein aggregates, mediates Targeted Protein Degradation and regulates cell-cycle transitions with its UDL activity.

molecular biology↗

bioRxiv2023

Molecular mechanisms for activation of the 26S proteasome

Various hormones, kinases, and stressors (fasting, heat shock) stimulate 26S proteasome activity. To understand how its capacity to degrade ubiquitylated protein can increase, we studied ZFAND5, which promotes protein degradation during muscle atrophy. Cryo-electron microscopy showed that ZFAND5 induces large conformational changes in the 19S regulatory particle. ZFAND5s AN1 Zn finger interacts with the Rpt5 ATPase and its C-terminus with Rpt1 ATPase and Rpn1, a ubiquitin-binding subunit. Surprisingly, these C-terminal interactions are sufficient to activate proteolysis. With ZFAND5 bound, entry into the proteasomes protein translocation channel is wider, and ZFAND5 dissociation causes opening of the 20S gate for substrate entry. Using single-molecular microscopy, we showed that ZFAND5 binds ubiquitylated substrates, prolongs their association with proteasomes, and increases the likelihood that bound substrates undergo degradation, even though ZFAND5 dissociates before substrate deubiquitylation. These changes in proteasome conformation and reaction cycle can explain the accelerated degradation and suggest how other proteasome activators may stimulate proteolysis.

molecular biology↗

bioRxiv2022

KaryoCreate: a new CRISPR-based technology to generate chromosome-specific aneuploidy by targeting human centromeres

Aneuploidy, the presence of chromosome gains or losses, is a hallmark of cancer and congenital syndromes. Here, we describe KaryoCreate (Karyotype CRISPR Engineered Aneuploidy Technology), a system that enables generation of chromosome-specific aneuploidies by co-expression of a sgRNA targeting chromosome-specific CENPA-binding [a]-satellite repeats together with dCas9 fused to a mutant form of KNL1. We designed unique and highly specific sgRNAs for 19 out of 24 chromosomes. Expression of these sgRNAs with KNL1Mut-dCas9 leads to missegregation and induction of gains or losses of the targeted chromosome in cellular progeny with an average efficiency of 8% and 12% for gains and losses, respectively (up to 20%), tested and validated across 9 chromosomes. Using KaryoCreate in colon epithelial cells, we show that chromosome 18q loss, a frequent occurrence in gastrointestinal cancers, promotes resistance to TGF{beta}, likely due to synergistic hemizygous deletion of multiple genes. Altogether, we describe a novel technology to create and study chromosome missegregation and aneuploidy in the context of cancer and beyond. HighlightsO_LIWe designed sgRNAs targeting chromosome-specific centromeres across 19 human chromosomes C_LIO_LIKaryoCreate combines chromosome-specific centromeric sgRNAs with dCas9 fused to a mutant form of KNL1. C_LIO_LIKaryoCreate allows engineering gains and losses of specific human chromosomes. C_LIO_LIEngineered Chromosome 18q loss promotes tumor-associated phenotypes in colon-derived cells. C_LIO_LIKaryoCreate is a CRISPR-based technology to foster the study of centromere biology and aneuploidy. C_LI

cell biology↗

bioRxiv2022

Localizing post-admixture adaptive variants with object detection on ancestry-painted chromosomes

Gene flow between previously isolated populations during the founding of an admixed or hybrid population has the potential to introduce adaptive alleles into the new population. If the adaptive allele is common in one source population, but not the other, then as the adaptive allele rises in frequency in the admixed population, genetic ancestry from the source containing the adaptive allele will increase nearby as well. Patterns of genetic ancestry have therefore been used to identify post-admixture positive selection in humans and other animals, including examples in immunity, metabolism, and animal coloration. A common method identifies regions of the genome that have local ancestry outliers compared to the distribution across the rest of the genome, considering each locus independently. However, we lack theoretical models for expected distributions of ancestry under various demographic scenarios, resulting in potential false positives and false negatives. Further, ancestry patterns between distant sites are often not independent. As a result, current methods tend to infer wide genomic regions containing many genes as under selection, limiting biological interpretation. Instead, we develop a deep learning object detection method applied to images generated from local ancestry-painted genomes. This approach preserves information from the surrounding genomic context and avoids potential pitfalls of user-defined summary statistics. We find the-method is robust to a variety of demographic misspecifications using simulated data. Applied to human genotype data from Cabo Verde, we localize a known adaptive locus to a single narrow region compared to multiple or long windows obtained using two other ancestry-based methods.

genomics↗

bioRxiv2020

Sex-biased admixture and assortative mating shape genetic variation and influence demographic inference in admixed Cabo Verdeans

Genetic data can provide insights into population history, but first we must understand the patterns that complex histories leave in genomes. Here, we consider the admixed human population of Cabo Verde to understand the patterns of genetic variation left by social and demographic processes. First settled in the late 1400s, Cabo Verdeans are admixed descendants of Portuguese colonizers and enslaved West African people. We consider Cabo Verdes well-studied historical record alongside genome-wide SNP data from 563 individuals from 4 regions within the archipelago. We use genetic ancestry to test for patterns of nonrandom mating and sex-specific gene flow, and we examine the consequences of these processes for common demographic inference methods and for genetic patterns. Notably, multiple population genetic tools that assume random mating underestimate the timing of admixture, but incorporating non-random mating produces estimates more consistent with historical records. We consider how admixture interrupts common summaries of genomic variation such as runs-of-homozygosity (ROH). While summaries of ROH may be difficult to interpret in admixed populations, differentiating ROH by length class shows that ROH reflect historical differences between the islands in their contributions from the source populations and post-admixture population dynamics. Finally, we find higher African ancestry on the X chromosome than on the autosomes, consistent with an excess of European males and African females contributing to the gene pool. Considering these genomic insights into population history in the context of Cabo Verdes historical record, we can identify how assumptions in genetic models impact inference of population history more broadly.

evolutionary biology↗

bioRxiv2020

Rapid adaptation to malaria facilitated by admixture in the human population of Cabo Verde

Humans have undergone large migrations over the past hundreds to thousands of years, exposing ourselves to new environments and selective pressures. Yet, evidence of ongoing or recent selection in humans is difficult to detect. Many of these migrations also resulted in gene flow between previously separated populations. These recently admixed populations provide unique opportunities to study rapid evolution in humans. Developing methods based on distributions of local ancestry, we demonstrate that this sort of genetic exchange has facilitated detectable adaptation to a malaria parasite in the admixed population of Cabo Verde within the last [~]20 generations. We estimate the selection coefficient is approximately 0.08, one of the highest inferred in humans. Notably, we show that this strong selection at a single locus has likely affected patterns of ancestry genome-wide, potentially biasing demographic inference. Our study provides evidence of adaptation in a human population on historical timescales.

evolutionary biology↗

bioRxiv2020

Simulating single-cell metabolism using a stochastic flux-balance analysis algorithm

Stochasticity from gene expression in single cells is known to drive metabolic heterogeneity at the level of cellular populations, which is understood to have important consequences for issues such as microbial drug tolerance and treatment of human diseases like cancer. Despite considerable advancements in profiling the genomes, transcriptomes, and proteomes of single cells, it remains difficult to experimentally characterise their metabolism at genome-scale. Computational methods could bridge this gap toward a systems understanding of single-cell biology. To address this challenge, we developed stochastic simulation algorithm with flux-balance analysis embedded (SSA-FBA), a computational framework for simulating the stochastic dynamics of the metabolism of individual cells using genome-scale metabolic models with experimental estimates of gene expression and enzymatic reaction rate parameters. SSA-FBA extends the constraint-based modelling formalism of metabolic network modelling to the single-cell regime, enabling simulation when experimentation is intractable. We also developed an efficient implementation of SSA-FBA that leverages the topology of embedded FBA models to significantly reduce the computational cost of simulation. As a preliminary case study, we built a reduced single-cell model of Mycoplasma pneumoniae, and used SSA-FBA to illustrate the role of stochasticity on the dynamics of metabolism at the single-cell level. SIGNIFICANCEDue to fundamental challenges limiting the experimental characterisation of metabolism within individual cells, computational methods are needed to help infer the metabolic behaviour of single cells from information about their transcriptomes and proteomes. In this paper, we present SSA-FBA, the first systematic framework for modelling the stochastic dynamics of single cells at the level of genome-scale metabolic reaction networks. We provide a robust and efficient algorithm for simulating SSA-FBA models, and apply it to a case study involving the metabolism, RNA and protein synthesis and turnover of a single Mycoplasma pneumoniae cell.

systems biology↗

bioRxiv2020

7,000 years of turnover: historical contingency and human niche construction shape the Caribbean's Anthropocene biota

The human-mediated movement of species across biogeographic boundaries--whether intentional or accidental--is dramatically reshaping the modern world. Yet, humans have been reshaping ecosystems and translocating species for millennia, and acknowledging the deeper roots of these phenomena is important for contextualizing present-day biodiversity loss, ecosystem functioning, and management needs. Here, we present the first database of terrestrial vertebrate species introductions spanning the entire anthropogenic history of a system: the Caribbean. We employ this ~7,000 year dataset to assess the roles of historical contingency and priority effects in shaping present-day community structure and conservation outcomes, finding that serial human colonization events contributed to habitat modifications and species extinctions that shaped the trajectories of subsequent species introductions by other human groups. We contextualized spatial and temporal patterns of species introductions within cultural practices and population histories of Indigenous, colonial, and modern human societies, and show that the taxonomic and biogeographic diversity of introduced species reflects diversifying reasons for species introductions through time. Recognition of the complex social and economic structures across the 7,000-year human history of the Caribbean provides the necessary context for interpreting the formation of an Anthropocene biota.

ecology↗