Biology subjects

Harris, R. M.

Publications and source records attributed to Harris, R. M..

13 recordsLinked to original sources

bioRxiv2025

Anti-CRISPR-mediated continuous directed evolution of CRISPR-Cas9 in human cells

Engineering CRISPR-Cas systems for improved or altered function is central to both research and therapeutic applications. Unfortunately most optimization, especially directed evolution in bacterial hosts, fails to capture the functional requirements of the complex mammalian cellular milieu, where activity is usually required. Robust strategies to enable continuous directed evolution of genome-targeting agents directly in human cells remain lacking. Here, we introduce CRISPR-MACE (Mammalian cell-enabled Adenovirus-assisted Continuous Evolution) as a foundational technology to address this need. CRISPR-MACE integrates virus-based continuous evolution with anti-CRISPR-based tunable selection to generate novel Streptococcus pyogenes Cas9 variants with both increased and decreased DNA binding capacity and nearly 1000-fold-enhanced resistance to AcrIIA4, the strongest known inhibitor of SpCas9. Notably, across independent evolution campaigns the same Cas9 gatekeeper mutation reproducibly emerged first, enabling subsequent adaptive steps along two interdependent axes of Cas9 function. In addition to advancing CRISPR technologies, this work establishes key principles and synthetic circuits for continuously evolving CRISPR-Cas systems directly in human cells. SIGNIFICANCE STATEMENTCRISPR technologies are typically engineered in bacteria, even though they must function in the far more complex environment of human cells. This gap has limited the discovery of variants with improved DNA recognition or with resistance to inhibitors that operate differently in mammalian systems. Here we establish CRISPR-MACE, a continuous evolution platform that leverages pressure from anti-CRISPR proteins to select Cas9 variants directly in human cells that have novel functions. Evolved variants show improvements in DNA binding strength and residence time, as well as striking escape from the potent Cas9 inhibitor AcrIIA4. Many anti-CRISPR proteins use distinct mechanisms, so our strategy can drive future continuous evolution campaigns in mammalian cells that expand the functional properties of genome-targeting agents.

synthetic biology↗

bioRxiv2025

Persistently increased expression of PKMzeta and unbiased gene expression profiles identify hippocampal molecular traces of a long-term active place avoidance memory and 'shadow' proteins

Long-term memory formation transiently activates Ca2+-calmodulin kinase II and atypical protein kinase C isoform iota/lambda, whereas persistent activation of the other atypical PKC, protein kinase M zeta (PKM{zeta}), together with its interacting partner, the scaffolding-protein KIBRA (Wwc1), are necessary for maintaining potentiated synapses and memory. Here, we use immediate-early gene (IEG) Arc activation during active place avoidance memory expression to tag memory-activated neurons with EYFP-ChR2. PKM{zeta} immunohistochemistry identified which hippocampal synaptic pathways are persistently altered. EYFP-PKM{zeta} colocalization persistently increases in the hippocampal trisynaptic pathway (dentate gyrus [DG][->]CA3[->]CA1) tracing a one-month-old PKM{zeta} engram. DG, CA3, and CA1 transcriptional profiling identifies that memory persistence correlates with upregulated immediate-early-genes Arc, Fos, and NPas4 in DG, but not with PKM{zeta} or most genes known to be crucial for LTP and memory. This rules out strong memory-related transcriptional regulation, but not regulation of mRNA translation or altered stability of "shadow proteins" like PKM{zeta} that, despite being crucial for memory maintenance, evade detection by unbiased transcriptome profiling. In contrast, our method Correlation Signal Co-cluster Reduction (C-SCoRe) incorporates weak linear and non-linear gene correlations and highlights network interaction changes predicting memory, and related IEG and Prkcz/Wwc1 expression. Manifold transcriptional relationships can reveal shadow molecular components of long-term memory.

neuroscience↗

bioRxiv2024

Independent effects of testosterone, estradiol, and sex chromosomes on gene expression in immune cells of trans- and cisgender individuals

The origins of sex differences in human disease are elusive, in part because of difficulties in separating the effects of sex hormones and sex chromosomes. To separate these variables, we examined gene expression in four groups of trans- or cisgender individuals: XX individuals treated with exogenous testosterone (n=21), XY treated with exogenous estradiol (n=13), untreated XX (n=20), and untreated XY (n=15). We performed single-cell RNA-sequencing of 358,426 peripheral blood mononuclear cells. Across the autosomes, 8 genes responded with a significant change in expression to testosterone, 34 to estradiol, and 32 to sex chromosome complement with no overlap between the groups. No sex-chromosomal genes responded significantly to testosterone or estradiol, but X-linked genes responded to sex chromosome complement in a remarkably stable manner across cell types. Through leveraging a four-state study design, we successfully separated the independent actions of testosterone, estradiol, and sex chromosome complement on genome-wide gene expression in humans.

genomics↗

bioRxiv2023

Evolutionary druggability: leveraging low-dimensional fitness landscapes towards new metrics for antimicrobial applications

The term "druggability" describes the molecular properties of drugs or targets in pharmacological interventions and is commonly used in work involving drug development for clinical applications. There are no current analogues for this notion that quantify the drug-target interaction with respect to a given target variants sensitivity across a breadth of drugs in a panel, or a given drugs range of effectiveness across alleles of a target protein. Using data from low-dimensional empirical fitness landscapes composed of 16 {beta}-lactamase alleles and seven {beta}-lactam drugs, we introduce two metrics that capture (i) the average susceptibility of an allelic variant of a drug target to any available drug in a given panel ("variant vulnerability"), and (ii) the average applicability of a drug (or mixture) across allelic variants of a drug target ("drug applicability"). Finally, we (iii) disentangle the quality and magnitude of interactions between loci in the drug target and the seven drug environments in terms of their mutation by mutation by environment (G x G x E) interactions, offering mechanistic insight into the variant variability and drug applicability metrics. Summarizing, we propose that our framework can be applied to other datasets and pathogen-drug systems to understand which pathogen variants in a clinical setting are the most concerning (low variant vulnerability), and which drugs in a panel are most likely to be effective in an infection defined by standing genetic variation in the pathogen drug target (high drug applicability).

systems biology↗

bioRxiv2021

Making Common Fund data more Findable: Catalyzing a Data Ecosystem

The Common Fund Data Ecosystem (CFDE) has created a flexible system of data federation that enables users to discover datasets from across the U.S. National Institutes of Health Common Fund without requiring that data owners move, reformat, or rehost those data. The CFDEs federation system is centered on a catalog that ingests metadata from individual Common Fund Programs Data Coordination Centers (DCCs) into a uniform metadata model that can then be indexed and searched from a centralized portal. This uniform Crosscut Metadata Model (C2M2) supports the wide variety of data types and metadata terms used by the individual DCCs and is designed to enable easy expansion to accommodate new data types. We describe its use to ingest and index data from ten DCCs.

bioinformatics↗

bioRxiv2021

Prolactin and prolactin receptor expression in the HPG axis and crop sac during parental care in both sexes of a biparental bird (Columba livia)

During breeding, multiple circulating hormones, including prolactin, facilitate reproductive transitions in species that exhibit parental care. Prolactin underlies parental behaviors and related physiological changes across many vertebrates, including birds and mammals. While circulating prolactin levels often fluctuate across breeding, less is known about how relevant target tissues vary in their prolactin responsiveness via prolactin receptor (PRLR) expression. Recent studies have also investigated prolactin (PRL) gene expression outside of the pituitary (i.e., extra-pituitary PRL), but how PRL gene expression varies during parental care in non-pituitary tissue (e.g., hypothalamus, gonads) remains largely unknown. Further, it is unclear if and how tissue-specific PRL and PRLR vary between the sexes during biparental care. To address this, we measured PRL and PRLR gene expression in tissues relevant to parental care, the endocrine reproductive hypothalamic-pituitary-gonadal (HPG) axis and the crop (a tissue with a similar function as the mammalian mammary gland), across various reproductive stages in both sexes of a biparental bird, the rock dove (Columba livia). We also assessed how these genes responded to changes in offspring presence by adding chicks mid-incubation, simulating an early hatch when prolactin levels were still moderately low. We found that pituitary PRL expression showed similar increases as plasma prolactin levels, and detected extra-pituitary PRL in the hypothalamus, gonads and crop. Hypothalamic and gonadal PRLR expression also changed as birds began incubation. Crop PRLR expression correlated with plasma prolactin, peaking when chicks hatched. In response to replacing eggs with a novel chick mid-incubation, hypothalamic and gonadal PRL and PRLR gene expression differed significantly compared to mid-incubation controls, even when plasma prolactin levels did not differ. We also found sex differences in PRL and PRLR that suggest gene expression may allow males to compensate for lower levels in prolactin by upregulating PRLR in all tissues. Overall, this study advances our understanding of how tissue-specific changes in responsiveness to parental hormones may differ across key reproductive transitions, in response to offspring cues, and between the sexes.

animal behavior and cognition↗

bioRxiv2021

Comparative Analysis of Emerging B.1.1.7+E484K SARS-CoV-2 isolates from Pennsylvania

Rapid whole genome sequencing of SARS-CoV-2 has presented the ability to detect new emerging variants of concern in near real time. Here we report the genome of a virus isolated in Pennsylvania in March 2021 that was identified as lineage B.1.1.7 (VOC-202012/01) that also harbors the E484K spike mutation, which has been shown to promote "escape" from neutralizing antibodies in vitro. We compare this sequence to the only 5 other B.1.1.7+E484K genomes from Pennsylvania, all of which were isolated in mid March. Beginning in February 2021, only a small number (n=60) of isolates with this profile have been detected in the US, and only a total of 253 have been reported globally (first in the UK in December 2020). Comparative genomics of all currently available high coverage B.1.1.7+E484K genomes (n=235) available on GISAID suggested the existence of 7 distinct groups or clonal complexes (CC; as defined by GNUVID) bearing the E484K mutation raising the possibility of 7 independent acquisitions of the E484K spike mutation in each background. Phylogenetic analysis suggested the presence of at least 3 distinct clades of B.1.1.7+E484K circulating in the US, with the Pennsylvanian isolates belonging to two distinct clades. Increased genomic surveillance will be crucial for detection of emerging variants of concern that can escape natural and vaccine induced immunity.

genomics↗

bioRxiv2020

Transcriptome analysis of hippocampal subfields identifies gene expression profiles associated with long-term active place avoidance memory

The hippocampus plays a critical role in storing and retrieving spatial information. By targeting the dorsal hippocampus and manipulating specific "candidate" molecules using pharmacological and genetic manipulations, we have previously discovered that long-term active place avoidance memory requires transient activation of particular molecules in dorsal hippocampus. These molecules include amongst others, the persistent kinases Ca-calmodulin kinase II (CaMKII) and the atypical protein kinase C isoform PKC{iota} /{lambda} for acquisition of the conditioned behavior, whereas persistent activation of the other atypical PKC, protein kinase M zeta (PKM{zeta}) is necessary for maintaining the memory for at least a month. It nonetheless remains unclear what other molecules and their interactions maintain active place avoidance long-term memory, and the candidate molecule approach is both impractical and inadequate to identify new candidates since there are so many to survey. Here we use a complementary approach to identify candidates by transcriptional profiling of hippocampus subregions after formation of the long-term active place avoidance memory. Interestingly, 24-h after conditioning and soon after expressing memory retention, immediate early genes were upregulated in the dentate gyrus but not Ammons horn of the memory expressing group. In addition to determining what genes are differentially regulated during memory maintenance, we performed an integrative, unbiased survey of the genes with expression levels that covary with behavioral measures of active place avoidance memory persistence. Gene Ontology analysis of the most differentially expressed genes shows that active place avoidance memory is associated with activation of transcription and synaptic differentiation in dentate gyrus but not CA3 or CA1, whereas hypothesis-driven candidate molecule analyses identified insignificant changes in the expression of many LTP-associated molecules in the various hippocampal subfields, nor did they covary with active place avoidance memory expression, ruling out strong transcriptional regulation but not translational regulation, which was not investigated. These findings and the data set establish an unbiased resource to screen for molecules and evaluate hypotheses for the molecular components of a hippocampus-dependent, long-term active place avoidance memory.

neuroscience↗

bioRxiv2019

Stress-mediated convergence of splicing landscapes in male and female Rock Doves

BackgroundThe process of alternative splicing provides a unique mechanism by which eukaryotes are able to produce numerous protein products from the same gene. Heightened variability in the proteome has been thought to potentiate increased behavioral complexity and response flexibility to environmental stimuli, thus contributing to more refined traits on which natural and sexual selection can act. While it has been long known that various forms of environmental stress can negatively affect sexual behavior and reproduction, we know little of how stress can affect the alternative splicing associated with these events, and less still about how splicing may differ between sexes. Using the model of the rock dove (Columba livia), our team previously uncovered sexual dimorphism in the basal and stress-responsive gene transcription of a biological system necessary for facilitating sexual behavior and reproduction, the hypothlamic-pituitary-gonadal (HPG) axis. In this study, we delve further into understanding the mechanistic underpinnings of how changes in the environment can affect reproduction by testing the alternative splicing response of the HPG axis to an external stressor in both sexes.\n\nResultsThis study reveals dramatic baseline differences in HPG alternative splicing between males and females. However, post submitting subjects to a restraint stress paradigm, we found a significant reduction in these differences between the sexes. In both stress and control treatments, we identified a higher incidence of splicing activity in the pituitary in both sexes as compared to other tissues. Of these splicing events, the core exon event is the most abundant form of splicing and more frequently occurs in the coding regions of the gene. Overall, we observed less splicing activity in the 3UTR end of transcripts than the 5UTR or coding regions.\n\nConclusionsOur results provide vital new insight into sex-specific aspects of the stress response on the HPG axis at an unprecedented proximate level. Males and females uniquely respond to stress, yet exhibit splicing patterns suggesting a convergent, optimal splicing landscape for stress response. This information has the potential to inform evolutionary theory as well as the development of highly-specific drug targets for stress-induced reproductive dysfunction.

genomics↗

bioRxiv2019

Molecular Profiling to Infer Neuronal Cell Identity: Lessons from small ganglia of the Crab Cancer borealis

Understanding circuit organization depends on identification of cell types. Recent advances in transcriptional profiling methods have enabled classification of cell types by their gene expression. While exceptionally powerful and high throughput, the ground-truth validation of these methods is difficult: if cell type is unknown, how does one assess whether a given analysis accurately captures neuronal identity? To shed light on the capabilities and limitations of solely using transcriptional profiling for cell type classification, we performed two forms of transcriptional profiling - RNA-seq and quantitative RT-PCR, in single, unambiguously identified neurons from two small crustacean networks: the stomatogastric and cardiac ganglia. We then combined our knowledge of cell type with unbiased clustering analyses and supervised machine learning to determine how accurately functionally-defined neuron types can be classified by expression profile alone. Our results demonstrate that expression profile is able to capture neuronal identity most accurately when combined with multimodal information that allows for post-hoc grouping so analysis can proceed from a supervised perspective. Solely unsupervised clustering can lead to misidentification and an inability to distinguish between two or more cell types. Therefore, our study supports the general utility of cell identification by transcriptional profiling, but adds a caution: it is difficult or impossible to know under what conditions transcriptional profiling alone is capable of assigning cell identity. Only by combining multiple modalities of information such as physiology, morphology or innervation target can neuronal identity be unambiguously determined.\n\nSIGNIFICANCE STATEMENTSingle cell transcriptional profiling has become a widespread tool in cell identification, particularly in the nervous system, based on the notion that genomic information determines cell identity. However, many cell type classification studies are unconstrained by other cellular attributes (e.g., morphology, physiology). Here, we systematically test how accurately transcriptional profiling can assign cell identity to well-studied anatomically- and functionally-identified neurons in two small neuronal networks. While these neurons clearly possess distinct patterns of gene expression across cell types, their expression profiles are not sufficient to unambiguously confirm their identity. We suggest that true cell identity can only be determined by combining gene expression data with other cellular attributes such as innervation pattern, morphology, or physiology.

neuroscience↗

bioRxiv2019

FAIRshake: toolkit to evaluate the findability, accessibility, interoperability, and reusability of research digital resources

As more datasets, tools, workflows, APIs, and other digital resources are produced by the research community, it is becoming increasingly difficult to harmonize and organize these efforts for maximal synergistic integrated utilization. The Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles have prompted many stakeholders to consider strategies for tackling this challenge by making these digital resources follow common standards and best practices so that they can become more integrated and organized. Faced with the question of how to make digital resources more FAIR, it has become imperative to measure what it means to be FAIR. The diversity of resources, communities, and stakeholders have different goals and use cases and this makes assessment of FAIRness particularly challenging. To begin resolving this challenge, the FAIRshake toolkit was developed to enable the establishment of community-driven FAIR metrics and rubrics paired with manual, semi- and fully-automated FAIR assessment capabilities. The FAIRshake toolkit contains a database that lists registered digital resources, with their associated metrics, rubrics, and assessments. The FAIRshake toolkit also has a browser extension and a bookmarklet that enables viewing and submitting assessments from any website. The FAIR assessment results are visualized as an insignia that can be viewed on the FAIRshake website, or embedded within hosting websites. Using FAIRshake, a variety of bioinformatics tools, datasets listed on dbGaP, APIs registered in SmartAPI, workflows in Dockstore, and other biomedical digital resources were manually and automatically assessed for FAIRness. In each case, the assessments revealed room for improvement, which prompted enhancements that significantly upgraded FAIRness scores of several digital resources.

bioinformatics↗

bioRxiv2017

Analysis of hippocampal transcriptomic responses to technical and biological perturbations

Cost-effective next-generation sequencing has made unbiased gene expression analysis possible. Single-neuron gene expression studies may be especially important for understanding nervous system structure and function because of the neuron-specific functionality and plasticity that defines functional neural circuits. Cellular dissociation is a prerequisite technical manipulation for single-cell and single cell-population studies, but the extent to which the cellular dissociation process cells affects neural gene expression has not been determined, nor has it been determined how gene expression is altered by the stress that accompanies many of the behavioral manipulations that are required to study learning and memory and other cognitive functions. Here, we determined to which extent cellular dissociation-induced changes in hippocampal gene expression might confound studies on the behavioral and physiological functions of the hippocampus. We processed tissue punch samples from the dentate gyrus (DG), CA3, and CA1 hippocampus subfields using either a tissue homogenization protocol or a cellular dissociation protocol in preparation for RNA sequencing analysis to evaluate the impact of the tissue preparation. Then, we evaluated the effect of stressful experience and cognitive training on hippocampus subfield specific gene expression and determined to which extent these response overlap with the cellular dissociation response. Finally, we assessed the extent to which the subfield-specific gene expression patterns are consistent with those identified in a recently published hippocampus subfield-specific gene expression database. We report substantial differences in baseline subfield-specific gene expression, that 1% of the hippocampal transcriptome is altered by the process of cellular dissociation, that an even weaker alteration is detected 24 h after stressful experience, and that while these alterations are largely distinct from the subfield specific response of the hippocampus transcriptome to cognitive training, there is nonetheless some important confounding overlap. These findings of the concordant and discordant effects of technical and behavioral manipulations should inform the design of future neural transcriptome studies and thus facilitate a more comprehensive understanding of hippocampal function.

neuroscience↗

bioRxiv2017

Single-Neuron Gene Expression Analysis Using the Maxwell 16 LEV System in the Neural Systems and Behavior Course

Gene expression analysis from single cells has become increasingly prominent across biological disciplines; thus, it is important to train students in these approaches. Here, we present an experimental and analysis pipeline that we developed for the Neural Systems & Behavior (NS&B) course at Marine Biological Laboratory. Our approach used the Maxwell(R) 16 LEV simplyRNA Tissue Kit and GoTaq(R) 2-Step RT-qPCR System for gene expression analysis from single neurons of the crustacean stomatogastric ganglion, a model system to study the generation of rhythmic motor patterns. We used double-stranded RNA to knockdown expression of a putative neuromodulator-activated sodium channel. We then examined the electrophysiological responses to known neuromodulators and confirmed that the response was reduced. Finally, we measured how mRNA levels of several ion channel genes changed in response. Our results provide new insights into the neural mechanisms underlying the generation and modulation of rhythmic motor patterns.

neuroscience↗