Biology subjects

Williams, S.

Publications and source records attributed to Williams, S..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Forming nephrons promote nephron progenitor maintenance and branching morphogenesis via paracrine BMP4 signalling under the control of Wnt4

Kidney development is known to be driven by interactions between stromal, nephron and ureteric epithelium progenitors in the nephrogenic niche. In contrast, the epithelial nephrons generated in this environment have largely been considered a product of niche rather than an active participant in the signalling interactions that maintain it. However, knockout of Wnt4, a gene required for nephron formation and stromal development, results in hypoplastic kidneys. We hypothesised that the forming nephron may play a role in maintaining the nephrogenic niche. In support of this hypothesis, conditional deletion of Wnt4 from the nephron lineage resulted in nephron progenitor dispersal and death, reduced branching morphogenesis and nephron progenitor cell number. Bulk and single cell transcriptional profiling of Wnt4 mutant kidneys revealed a downregulation of BMP signalling effectors Id1, and Id3 in nephron progenitor cells, implicating Wnt4 target BMP4 as a paracrine signal mediating feedback from the committing nephron. Recombinant BMP4 restored nephron progenitor compaction in cultured Wnt4 mutant kidneys and blocked differentiation in wildtype controls mirroring the role of BMP7-MAPK signalling in progenitor self-renewal. Our data supports a revised model of the nephrogenic niche in which forming nephrons promote progenitor maintenance and branching morphogenesis, in part via paracrine BMP4 signalling under the control of Wnt4. This requirement for nephron-derived signals for maintenance of the nephrogenic niche provides new mechanistic insight into kidney morphogenesis and human renal hypodysplasia phenotypes associated with deleterious WNT4 mutations.

developmental biology↗

bioRxiv2023

A population code for idiothetic representations in the hippocampal-septal circuit

The hippocampus is a higher-order brain structure responsible for encoding new episodic memories and predicting future outcomes. In absence of external stimuli, neurons in the hippocampus express sequential activities which have been proposed to support path integration by tracking elapsed time, distance traveled, and other idiothetic variables. On the other hand, with sufficient external sensory inputs, hippocampal neurons can fire with respect to allocentric cues. Previously, these idiothetic codes have been described in conditions where running speed is clamped experimentally. To this day, the exact determinants of idiothetic representations during free navigation remain unclear. Additionally, whether CA1 and CA3 temporal and distance codes are transmitted downstream to the lateral septum has not been established. Here, we develop an unsupervised model trained to compress neural information with minimal loss, and find that we can efficiently decode elapsed time and distance traveled from low-dimensional embeddings of neural activity in freely moving mice. We also developed unbiased information metrics that are minimally sensitive to quantization parameters and enable comparisons across modalities and brain regions. In more than 30,000 CA1 pyramidal neurons, we show that spatiotemporal information is represented as a mixture of idiothetic and allocentric information, the balance of which is dictated by task demand and environmental conditions. In particular, we find that a subset of CA1 pyramidal neurons encode the spatiotemporal distance to rewards. Single cell and population statistics across the hippocampal-septal circuit reveal that idiothetic variables emerge in CA1 and are integrated postsynaptically in the lateral septum. Finally, we implement a computational model trained to replicate real world neural activity, and find that grid cells could provide a plausible input for CA1 representations of time and distance. Altogether, our results suggest that hippocampal CA1 continuously integrates both idiothetic and allocentric signals depending on task demand and available cues, and these high-level representations are effectively transmitted to downstream regions.

neuroscience↗

bioRxiv2023

Precise Therapeutic Targeting of Distinct NRXN1+/- Mutations

Given the large number of genes significantly associated with risk for neuropsychiatric disorders, a critical unanswered question is the extent to which diverse mutations --sometimes impacting the same gene--will require tailored therapeutic strategies. Here we consider this in the context of rare neuropsychiatric disorder-associated copy number variants (2p16.3) resulting in heterozygous deletions in NRXN1, a pre-synaptic cell adhesion protein that serves as a critical synaptic organizer in the brain. Complex patterns of NRXN1 alternative splicing are fundamental to establishing diverse neurocircuitry, vary between the cell types of the brain, and are differentially impacted by unique (non-recurrent) deletions. We contrast the cell-type-specific impact of patient-specific mutations in NRXN1 using human induced pluripotent stem cells, finding that perturbations in NRXN1 splicing result in divergent cell-type-specific synaptic outcomes. Via distinct loss-of-function (LOF) and gain-of-function (GOF) mechanisms, NRXN1+/- deletions cause decreased synaptic activity in glutamatergic neurons, yet increased synaptic activity in GABAergic neurons. Reciprocal isogenic manipulations causally demonstrate that aberrant splicing drives these changes in synaptic activity. For NRXN1 deletions, and perhaps more broadly, precision medicine will require stratifying patients based on whether their gene mutations act through LOF or GOF mechanisms, in order to achieve individualized restoration of NRXN1 isoform repertoires by increasing wildtype, or ablating mutant isoforms. Given the increasing number of mutations predicted to engender both LOF and GOF mechanisms in brain disorders, our findings add nuance to future considerations of precision medicine.

neuroscience↗

bioRxiv2023

go_batch: A snakemake pipeline to assemble mitochondrial and ribosomal sequences from genome skims

Low coverage "genome-skims" are often used to assemble organelle genomes and ribosomal gene sequences for cost effective phylogenetic and barcoding studies. Natural history collections hold invaluable biological information, yet poor preservation resulting in degraded DNA often hinders PCR based analyses. However, with improvements to molecular techniques and sequencing technology, it is possible to use methods developed for working with ancient DNA to generate libraries and sequence the short fragments typical of degraded DNA to generate genome skims from museum collections. Here we introduce a snakemake toolkit comprised of three pipelines skim2mt, skim2rrna and gene2phylo, designed to unlock the genomic potential of historical museum specimens using genome skimming. Specifically, skim2mt and skim2rrna perform the batch assembly, annotation and phylogenetic analysis of mitochondrial genomes and nuclear ribosomal genes, respectively, from low-coverage genome skims. The third pipeline gene2phylo takes a set of gene alignments and performs phylogenetic analysis of individual genes, partitioned analysis of concatenated alignments and a phylogenetic analysis based on gene trees. We benchmark our pipelines with simulated data, followed by testing with a novel genome skimming dataset from both recent and historical solariellid gastropod samples. We show that the toolkit can recover mitochondrial and ribosomal genes from poorly preserved museum specimens of the gastropod family Solariellidae. In addition, the phylogenetic analysis of multiple gene sequences is consistent with our current understanding of taxonomic relationships. The generation of bioinformatic pipelines that facilitate processing large quantities of sequence data from the vast repository of specimens held in natural history museum collections will greatly aid species discovery and exploration of biodiversity over time, ultimately aiding conservation efforts in the face of a changing planet.

bioinformatics↗

bioRxiv2023

Ancient Mongolian aurochs genomes reveal sustained introgression and management in East Asia

Societies in East Asia have utilized domesticated cattle for over 5000 years, but the genetic history of cattle in East Asia remains understudied. Genome-wide analyses of 23 ancient Mongolian cattle reveal that East Asian aurochs and ancient East Asian taurine cattle are closely related, but neither are closely related to any modern East Asian breeds. We observe binary variation in aurochs diet throughout the early Neolithic, and genomic evidence shows millennia of sustained male-dominated introgression. We identify a unique connection between ancient Mongolian aurochs and the European Hereford breed. These results point to the likelihood of human management of aurochs in Northeast Asia prior to and during the initial adoption of taurine cattle pastoralism. One-Sentence SummaryAncient interbreeding of East Asian aurochs and cattle suggests management, but leaves no signature in modern eastern breeds.

genomics↗

bioRxiv2023

Assessing the activity of different plant-derived molecules and potential biological nitrification inhibitors on a range of soil ammonia- and nitrite- oxidizing strains

Nitrification is associated with significant losses of fertilizer-derived ammonium from agroecosystems. The use of biological nitrification inhibitors (BNIs), in place of synthetic nitrification inhibitors (SNIs), holds a great potential to effectively reduce N losses and conforms with the current move towards ecological-intensified agriculture. Knowledge of the activity of BNIs to soil nitrifiers is limited and is mostly based on bioassays with a single Nitrosomonas europaea strain. We determined the in vitro activity of multiple plant-derived compounds as BNIs like (i) root-derived compounds (sakuranetin, MHPP, and zeanone); (ii) other phytochemicals (caffeic acid, quinic acid, chlorogenic acid and shikimic acid), and (iii) analogues of statins (simvastatin), triazoles (1-butyl-4-propyl-triazole, 1,4-dibutyltriazole) and zeanone (2-methoxy-1,4-naphthoquinone), on ecophysiologically and phylogenetically distinct soil-derived ammonia-oxidizing bacteria (AOB) (Nitrosospira multiformis and N. europaea), ammonia-oxidizing archaea (AOA) (Candidatus Nitrosotalea sinensis and Candidatus Nitrosocosmicus franklandianus), and a nitrite-oxidizing bacterium (NOB) (Nitrobacter sp. NHB1). AOA were more sensitive than AOB to BNIs. Sensitivity within AOA group was BNI-dependent, unlike AOB for which N. multiformis was consistently more sensitive than N. europaea. Interestingly, several compounds were inhibitory to Nitrobacter sp. with MHPP and caffeic acid being more potent to the NOB compared to the AOB and AOA strains, an observation with potentially serious implications for soil quality and agricultural production. Overall, zeanone, MHPP and caffeic acid were the most potent BNIs towards AOB, zeanone and 2-methoxy-1,4-naphthoquinone were the most effective compounds against AOA, while caffeic acid was the most potent BNI on Nitrobacter sp. We provide pioneering evidence for the activity range of multiple BNIs on soil nitrifiers, stress the need for revisiting the biological screening systems currently used for BNI determination and we sought for a more thorough monitoring of the impact of BNI candidates on a range of both target and non-target microorganisms.

microbiology↗

bioRxiv2023

Genomic epidemiology of third-generation cephalosporin-resistant Escherichia coli from Argentinian pig and dairy farms reveals animal-specific patterns of co-resistance and resistance mechanisms

Control measures are being introduced globally to reduce the prevalence of antibiotic resistant (ABR) bacteria on farms. However, little is known about the current prevalence and molecular ecology of ABR in key opportunistic human pathogens such as Escherichia coli on South American farms. Working with 30 dairy cattle farms and 40 pig farms across two provinces in central-eastern Argentina, we report a comprehensive genomic analysis of third-generation cephalosporin resistance (3GC-R) in E. coli. 3GC-R isolates were recovered from 34.8% (cattle) and 47.8% (pigs) of samples from faecally contaminated sites. Phylogenetic analysis revealed substantial diversity suggestive of long-term horizontal transmission of 3GC-R mechanisms. Despite this, mechanisms such as CTX-M-15 and CTX-M-2 were detected more often in dairy farms, while CTX-M-8 and CMY-2, and co-carriage of amoxicillin/clavulanate resistance and florfenicol resistance were more commonly detected in pig farms. This suggests different selective pressures of antibiotic use in these two animal types, particularly the balance of fourth-versus third-generation cephalosporin use, and of amoxicillin/clavulanate and florfenicol use. We identified the {beta}-lactamase gene blaROB in 3GC-R E. coli, which has previously only been reported in the family Pasteurellaceae, including farmed animal pathogens. blaROB was found alongside a novel florfenicol resistance gene - ydhC - also mobilised from a pig pathogen as part of a new plasmid-mediated composite transposon, which is already widely disseminated. These data set a baseline from which to measure the effects of interventions aimed at reducing on-farm ABR and provide an opportunity to investigate zoonotic transmission of resistant bacteria in this region. ImportanceLittle is known about the ecology of critically important antibiotic resistance among opportunistic human pathogens (e.g. Escherichia coli) on South American farms. By studying 70 farms in central-eastern Argentina, we identified that third-generation cephalosporin resistance (3GC-R) in E. coli was mediated by mechanisms seen more often in certain species (pigs or dairy cattle) and that 3GC-R pig E. coli were more likely to be co-resistant to florfenicol and amoxicillin/clavulanate. This suggests that on-farm antibiotic usage is key to selecting the types of E. coli present on these farms. 3GC-R E. coli were highly phylogenetically variable and we identified the de novo mobilisation of the resistance gene blaROB, alongside a novel florfenicol resistance gene, from pig pathogens into E. coli on a mobile genetic element that was widespread in the study region. Overall, this shows the importance of surveying poorly studied regions for critically important antibiotic resistance which might impact human health.

microbiology↗

bioRxiv2023

A robust Platform for Integrative Spatial Multi-omics Analysis to Map Immune Responses to SARS-CoV-2 infection in Lung Tissues

The SARS-CoV-2 (COVID-19) virus has caused a devastating global pandemic of respiratory illness. To understand viral pathogenesis, methods are available for studying dissociated cells in blood, nasal samples, bronchoalveolar lavage fluid, and similar, but a robust platform for deep tissue characterisation of molecular and cellular responses to virus infection in the lungs is still lacking. We developed an innovative spatial multi-omics platform to investigate COVID-19-infected lung tissues. Five tissue-profiling technologies were combined by a novel computational mapping methodology to comprehensively characterise and compare the transcriptome and targeted proteome of virus infected and uninfected tissues. By integrating spatial transcriptomics data (Visium, GeoMx and RNAScope) and proteomics data (CODEX and PhenoImager HT) at different cellular resolutions across lung tissues, we found strong evidence for macrophage infiltration and defined the broader microenvironment surrounding these cells. By comparing infected and uninfected samples, we found an increase in cytokine signalling and interferon responses at different sites in the lung and showed spatial heterogeneity in the expression level of these pathways. These data demonstrate that integrative spatial multi-omics platforms can be broadly applied to gain a deeper understanding of viral effects on cellular environments at the site of infection and to increase our understanding of the impact of SARS-CoV-2 on the lungs.

bioinformatics↗

bioRxiv2022

Using passive acoustic monitoring to estimate the abundance of wide-ranging species in tropical rainforest ecosystems

Most conservation relies on being able to estimate population size accurately. The development, implementation and adaptation of effective conservation strategies rely on quantifying the impacts of different threats on population dynamics, identifying species that need conservation management, and providing feedback on the effectiveness of any management actions. However, current approaches are not suitable for wide-ranging species that reside in tropical ecosystems. Here we use the great green macaw Ara ambiguus as a case study to show that passive acoustic monitoring is an effective tool for collecting data that can then estimate abundance. We estimate a population of 485.65 {+/-} 61 SE great green macaws in Costa Rica during the breeding, suggesting the population here is larger than previously estimated. We have also highlighted potentially important areas for the species in regions that had not previously been studied. We have demonstrated at a population scale that passive acoustic monitoring (PAM) offers conservationists an efficient and effective way to understand population dynamics. With a high proportion of parrot species threatened globally, passive acoustic monitoring will enable effective monitoring and become an essential tool in conservation planning and evaluation. PAM technology has enormous potential to facilitate such assessments because it is easily scalable, recordings can be stored and re-analysed as machine learning, and abundance estimation techniques become more advanced.

ecology↗

bioRxiv2022

Reduced specification of lateral plate mesoderm progenitors underpins heterochronic development of the emu wing

The tetrapod limb has evolved a broad diversity of form and function, enabling vertebrates to adapt to a wide range of environments. One of the most striking examples of this is the evolution of powered flight in birds. However, during the avian radiation, flightless ratites (Paleognathae) secondarily evolved multiple instances of wing reductions, utilizing distinct molecular mechanisms, and displaying heterochrony with flighted birds (Neoaves). Among ratites, the emu displays the most marked reduction of wing anatomy, developing a small wing with a single clawed digit. This major divergence from the typical avian pattern provides a robust model to determine the mechanisms underpinning developmental plasticity in the tetrapod limb. To interrogate the ontogenetic origins of vestigial wing development, we applied comparative single cell transcriptomics of the embryonic emu forelimb field with the chicken, as it possess a typical wing. Stunted wing development in the emu occurs through a heterotopic reduction of lateral plate mesoderm (LPM)-derived limb progenitor cells, and accompanying downregulation of genes associated with LPM development and early limb initiation. Here, forelimb bud initiation and outgrowth is altered by changes to the specification and allocation of limb progenitor cells, acting as an underlying template for pre- and post-patterning mechanisms. These findings provide novel insights into the evolution of limb development in tetrapods, and emphasizes an important, yet underappreciated role for heterotopy as major driver of limb disparity. Significance statementAnimals exhibit a striking variety of morphologies, yet our understanding of how these forms evolve and arise during development are lagging. The emu is a large, flightless bird which has evolved a vestigial wing. This model allows detailed interrogations into the mechanisms which underlie evolution and development of a distinct morphological structure. Through application of comparative single cell transcriptomics between the emu and chicken, we identify an early embryological mechanism, heterotopy, underlying the evolution and vestigial development of the emu wing. This mechanism features reduced allocation of limb bud progenitor cells in the lateral plate mesoderm (LPM). This data provides new information on the mechanisms that underpin evolutionary diversity in morphological features.

evolutionary biology↗

bioRxiv2022

Improving the preclinical and clinical success rates of LMW drugs depends on radical revisions to the status quo scientific foundations of medicinal chemistry: a case study on COVID Mpro inhibition

The poor preclinical and clinical success rates of low molecular weight (LMW) compounds can be partially attributed to the inherent trial-and-error nature of pharmaceutical research, which is limited largely to retrospective data-driven, rather than prospective prediction-driven human relevant workflows stemming from: 1) inadequate scientific understanding of structure-activity, structure-property, and structure-free energy relationships; 2) disconnects between empirical models derived from in vitro equilibrium data (e.g., Hill and Michaelis-Menten models) vis-a-vis the native non-equilibrium cellular setting (where the pertinent metrics consist of rates, rather than equilibrium state distributions); and 3) inadequate understanding of the non-linear dynamic (NLD) basis of cellular function and disease. We argue that the limit of understanding of cellular function/dysfunction and pharmacology based on empirical principles (observation/inference) has been reached, and that further progress depends on understanding these phenomena at the first principles theoretical level. Toward that end, we have been developing and applying a theory (called "Biodynamics") on the general mechanisms by which: 1) cellular functions are conveyed by dynamic multi-molecular/-ionic (multi-flux) systems operating in the NLD regime; 2) cellular dysfunction results from molecular dysfunction; 3) molecular structure and function are powered by covalent/non-covalent forms of free energy; and 4) cellular dysfunction is corrected pharmacologically. Biodynamics represents a radical departure from the status quo empirical science and reduction to practice thereof, replacing: 1) the interatomic contact model of structure-free energy and structure-property relationships with a solvation free energy model; 2) equilibrium drug-target occupancy models with dynamic models accounting for time-dependent drug and target/off-target binding site buildup and decay; and 3) linear models of molecular structure-function and multi-molecular/-ionic systems conveying cellular function and dysfunction with NLD models that more realistically capture the emergent non-linear behaviors of such systems. Here, we apply our theory to COVID Mpro inhibition and overview its implications for a holistic, in vivo relevant approach to drug design.

pharmacology and toxicology↗

bioRxiv2022

Spatial memory consolidation during REM sleep requires stabilization of newly formed place cells.

The involvement of rapid-eye-movement sleep (REMs) in spatial memory formation was recently demonstrated, although how neural activity during REMs influences newly-formed place field stability remains unclear. Here, we combined large-scale single-unit recordings of mouse hippocampal CA1 with an established optogenetic approach enabling REMs-selective inhibition of medial septum GABAergic neurons (MSGABA), resulting in spatial memory deficits when applied post-learning. Although individual neural activity was unaffected by REMs-selective MSGABA inhibition during a post-learning rest session, both the synchrony of population-level activity bursts observed during REMs occurring in the rest session and place field stability measured during subsequent memory recall testing were reduced vs controls. However, the latter effect was limited to place cells participating in population activity during REMs, as stability of non-participant place cells was relatively weak and indifferent between groups. This suggests that synchronous CA1 population activity during REMs stabilizes spatial representations in a plastic subpopulation of participating CA1 neurons.

neuroscience↗

bioRxiv2022

High resolution mapping of the breast cancer tumor microenvironment using integrated single cell, spatial and in situ analysis of FFPE tissue

Single cell and spatial technologies that profile gene expression across a whole tissue are revolutionizing the resolution of molecular states in clinical tissue samples. Commercially available methods that characterize either single cell or spatial gene expression are currently limited by low sample throughput and/or gene plexy, lack of on-instrument analysis, and the destruction of histological features and epitopes during the workflow. Here, we analyzed large, serial formalin-fixed, paraffin-embedded (FFPE) human breast cancer sections using a novel FFPE-compatible single cell gene expression workflow (Chromium Fixed RNA Profiling; scFFPE-seq), spatial transcriptomics (Visium CytAssist), and automated microscopy-based in situ technology using a 313-plex gene panel (Xenium In Situ). Whole transcriptome profiling of the FFPE tissue using scFFPE-seq and Visium facilitated the identification of 17 different cell types. Xenium allowed us to spatially resolve these cell types and their gene expression profiles with single cell resolution. Due to the non-destructive nature of the Xenium workflow, we were able to perform H&E staining and immunofluorescence on the same section post-processing which allowed us to spatially register protein, histological, and RNA data together into a single image. Integration of data from Chromium scFFPE-seq, Visium, and Xenium across serial sections allowed us to do extensive benchmarking of sensitivity and specificity between the technologies. Furthermore, data integration inspired the interrogation of three molecularly distinct tumor subtypes (low-grade and high-grade ductal carcinoma in situ (DCIS), and invasive carcinoma). We used Xenium to characterize cellular composition and differentially expressed genes within these subtypes. This analysis allowed us to draw biological insights about DCIS progression to infiltrating carcinoma, as the myoepithelial layer degrades and tumor cells invade the surrounding stroma. Xenium also allowed us to further predict the hormone receptor status of tumor subtypes, including a small 0.1 mm2 DCIS region that was triple positive for ESR1 (estrogen receptor), PGR (progesterone receptor), and ERBB2 (human epidermal growth factor receptor 2, a.k.a. HER2) RNA. In order to derive whole transcriptome information from these cells, we used Xenium data to interpolate the cell composition of Visium spots, and used Visium whole transcriptome information to discover new biomarkers of breast tumor subtypes. We demonstrate that scFFPE-seq, Visium, and Xenium independently provide information about molecular signatures relevant to understanding cancer heterogeneity. However, it is the integration of these technologies that leads to even deeper insights, ushering in discoveries that will progress oncology research and the development of diagnostics and therapeutics.

cancer biology↗

bioRxiv2022

Remodelling of carbon metabolism during sulfoglycolysis in Escherichia coli

Sulfoquinovose (SQ) is a major metabolite in the global sulfur cycle produced by nearly all photosynthetic organisms. One of the major pathways involved in the catabolism of SQ in bacteria, such as Escherichia coli, is a variant of the glycolytic Embden-Meyerhof-Parnas (EMP) pathway termed the sulfoglycolytic EMP (sulfo-EMP) pathway, which leads to consumption of three of the six carbons of SQ and excretion of 2,3-dihydroxypropanesulfonate (DHPS). Comparative metabolite profiling of aerobically Glc-grown and SQ-grown E. coli was undertaken to identify the metabolic consequences of switching from glycolysis to sulfoglycolysis. Sulfoglycolysis was associated with the diversion of triose-phosphates to synthesize sugar phosphates (gluconeogenesis), and an unexpected accumulation of trehalose and glycogen storage carbohydrates. Sulfoglycolysis was also associated with global changes in central carbon metabolism, as indicated by changes in levels of intermediates in the tricarboxylic acid (TCA) cycle, the pentose phosphate pathway (PPP), polyamine metabolism, pyrimidine metabolism and many amino acid metabolic pathways. Upon entry into stationary phase and depletion of SQ, E. coli utilize their glycogen, indicating a reversal of metabolic fluxes to allow glycolytic metabolism. ImportanceThe sulfosugar sulfoquinovose is estimated to be produced on a scale of 10 billion tonnes per annum, making it a major organosulfur species in the biosulfur cycle. Microbial degradation of sulfoquinovose through sulfoglycolysis allows utilization of its carbon content and contributes to biomineralization of its sulfur. However, the metabolic consequences of microbial growth on sulfoquinovose are unclear. We use metabolomics to identify the metabolic adaptations that Escherichia coli undergoes when grown on sulfoquinovose versus glucose. This revealed increased flux into storage carbohydrates through gluconeogenesis, and reduced flux of carbon into the TCA cycle and downstream metabolism. These changes are relieved upon return to stationary phase growth and reversion to glycolytic metabolism. This work provides s new insights into the metabolic consequences of microbial growth on an abundant sulfosugar.

biochemistry↗

bioRxiv2022

Treatment-mediated selection of lethal prostate cancer clones defined by copy number architectures

Despite initial responses to hormone treatment, metastatic prostate cancer invariably evolves to a lethal state. To characterize the intra-patient relationships of metastases that evade treatment, we performed genomewide copy number profiling and bespoke approaches targeting the androgen receptor (AR) on 142 metastatic regions from 10 organs harvested post-mortem from nine men who died from prostate cancer. We identified diverse and patient-unique alterations clustering around the AR in metastases from every patient with evidence of independent acquisition of related genomic changes within an individual and, in some patients, the co-existence of AR-neutral clones. Using the genomic boundaries of pan-autosome copy number change, we confirmed a common clone of origin across metastases and diagnostic biopsies; and identified in individual patients, clusters of metastases occupied by dominant clones with diverged autosomal copy number alterations. Autosome-defined clusters were characterized by cluster-specific AR gene architectures that in two index cases were topologically more congruent than by chance (p-values 0.03, 3.07x10-8). Integration with anatomical site suggested patterns of spread and points of genomic divergence. Copy number boundaries identified treatment-selected clones with putatively distinct lethal trajectories. Statement of significanceLethal prostate cancer evolves from a single clone of origin and upon a treatment-mediated selection, progresses to lethal disease via a limited number of related clones harboring patient-unique androgen receptor gene architectures.

cancer biology↗

bioRxiv2022

Dorsal Hippocampus To Nucleus Accumbens Projections Drive Reinforcement Via Activation of Accumbal Dynorphin Neurons.

The hippocampus represents a key structure in the integration of emotional processing, learning and memory, and reward-related behaviors. While the ventral subdivision of the hippocampus (vHPC) is involved in processing emotional values of salient stimuli and goal-directed behaviors, the dorsal hippocampus (dHPC) plays a critical role in episodic, spatial, and associative memory. In addition, it has been shown that the dHPC is necessary for context- and cue-associated reward behaviors, including the expression of reward seeking. The nucleus accumbens (NAc), a central structure in the mesolimbic reward pathway, integrates the salience of aversive and rewarding stimuli and its activity is sufficient to drive aversive and appetitive behaviors. Recent evidence has demonstrated that dHPC[->]Nucleus Accumbens (NAc) pathway is necessary for expression of a conditioned place preference. However, despite years of groundbreaking research and identification of direct projections from the dHPC to the NAc, the sufficiency for dHPC[->]NAC inputs to drive reinforcement and reward associated behavior remains to be determined. Here using a wide range of complementary and cutting-edge techniques including behavior, in-vivo manipulation using optogenetics, chemogenetics, brain clearing, local field potential and fiber photometry recordings, we demonstrate that activation of excitatory projections from the CA1 subregion of the dHPC (dCA1) is sufficient to drive reinforcing behaviors. In addition, we provide strong evidence that this reinforcing behavior is driven by 1) a direct projection from the dCA1 to the NAc and 2) enhanced glutamatergic signaling within the NAc. Furthermore, we uncovered that while dCA1 stimulation increases the activity of both enkephalin- and dynorphin-containing medium spiny neurons in the NAc, the selective activity of dynorphin-containing neurons is necessary for the expression of this reinforcing behavior. Our findings shed light on a novel pathway governing reinforcement and further extend the role of the dHPC on reward seeking.

neuroscience↗

bioRxiv2022

Spatial transcriptomics of FFPE pancreatic intraepithelial neoplasias reveals cellular and molecular alterations of progression to pancreatic ductal carcinoma

Spatial transcriptomics (ST) is a powerful new approach to characterize the cellular and molecular architecture of the tumor microenvironment. Previous single-cell RNA-sequencing (scRNA-seq) studies of pancreatic ductal adenocarcinoma (PDAC) have revealed a complex immunosuppressive environment characterized by numerous cancer associated fibroblasts (CAFs) subtypes that contributes to poor outcomes. Nonetheless, the evolutionary processes yielding that microenvironment remain unknown. Pancreatic intraepithelial neoplasia (PanIN) is a premalignant lesion with potential to develop into PDAC, but the formalin-fixed and paraffin-embedded (FFPE) specimens required for PanIN diagnosis preclude scRNA-seq profiling. We developed a new experimental pipeline for FFPE ST analysis of PanINs that preserves clinical specimens for diagnosis. We further developed novel multi-omics analysis methods for threefold integration of imaging, ST, and scRNA-seq data to analyze the premalignant microenvironment. The integration of ST and imaging enables automated cell type annotation of ST spots at a single-cell resolution, enabling spot selection and deconvolution for unique cellular components of the tumor microenvironment (TME). Overall, this approach demonstrates that PanINs are surrounded by the same subtypes of CAFs present in invasive PDACs, and that the PanIN lesions are predominantly of the classical PDAC subtype. Moreover, this new experimental and computational protocol for ST analysis suggests a biological model in which CAF-PanIN interactions promote inflammatory signaling in neoplastic cells which transitions to proliferative signaling as PanINs progress to PDAC. SummaryPancreatic intraepithelial neoplasia (PanINs) are pre-malignant lesions that progress into pancreatic ductal adenocarcinoma (PDAC). Recent advances in single-cell technologies have allowed for detailed insights into the molecular and cellular processes of PDAC. However, human PanINs are stored as formalin-fixed and paraffin-embedded (FFPE) specimens limiting similar profiling of human carcinogenesis. Here, we describe a new analysis protocol that enables spatial transcriptomics (ST) analysis of PanINs while preserving the FFPE blocks required for clinical assessment. The matched H&E imaging for the ST data enables novel machine learning approaches to automate cell type annotations at a single-cell resolution and isolate neoplastic regions on the tissue. Transcriptional profiles of these annotated cells enable further refinement of imaging-based cellular annotations, showing that PanINs are predominatly of the classical subtype and surrounded by PDAC cancer associated fibroblast (CAF) subtypes. Applying transfer learning to integrate ST PanIN data with PDAC scRNA-seq data enables the analysis of cellular and molecular progression from PanINs to PDAC. This analysis identified a transition between inflammatory signaling induced by CAFs and proliferative signaling in PanIN cells as they become invasive cancers. Altogether, this integration of imaging, ST, and scRNA-seq data provides an experimental and computational approach for the analysis of cancer development and progression.

cancer biology↗

bioRxiv2022

Deep-Learning for Automated Markerless Tracking of Infants General Movements

The presence of abnormal infant General Movements (GMs) is a strong predictor of progressive neurodevelopmental disorders, including cerebral palsy (CP). Automation of the assessment will overcome scalability barriers that limit its delivery to at-risk individuals. Here, we report a robust markerless pose-estimation scheme, based on advanced deep-learning technology, to track infant movements in consumer mobile device video recordings. Two deep neural network models, namely Efficientnet-b6 and resnet152, were trained on manually annotated data across twelve anatomical locations (3 per limb) in 12 videos from 6 full-term infants (mean age = 17.33 (SD 2.9) wks, 4 male, 2 female), using the DeepLabCut framework. K-fold cross-validation indicates the generalization capability of the deep-nets for GM tracking on out-of-domain data with an overall performance of 95.52% (SD 2.43) from the best performing model (Efficientnet-b6) across all infants (performance range: 84.32- 99.24% across all anatomical locations). The paper further introduces an automatic, unsupervised strategy for performance evaluation on extensive out-of-domain recordings through a fusion of likelihoods from a Kalman filter and the deep-net. Findings indicate the possibility of establishing an automated GM tracking platform, as a suitable alternative to, or support for, the current observational protocols for early diagnosis of neurodevelopmental disorders in early infancy.

bioengineering↗