Biology subjects

Mah, A.

Publications and source records attributed to Mah, A..

11 recordsLinked to original sources

bioRxiv2026

Phase response curve and RNA-sequencing demonstrate spiders' sensitivity to light and pinpoint candidate light-responsive genes

Spiders can maintain a wide range of free-running periods while still being entrained to a 24-hour day. To investigate the underlying mechanism of this entrainment, we constructed the phase-response curve (PRC) for the orb weaver, Metazygia wittfeldae, by subjecting the spiders to one-hour light pulses at various times throughout the circadian day. The resulting type 0 PRC showed high amplitude (> 6 hour) phase advance and delays when the light pulse was applied during circadian time (CT) 16-18, with a break point of advances to delays at CT 17. We then investigated the genetic mechanism of the phase response to light by splitting M. wittfeldae adult females entrained to 12 hours light:12 hours dark (LD 12:12) into two groups. One group received a 1-hour light pulse 5 hours after lights off (CT17), and one group did not. We then sacrificed spiders for RNA isolations 1 and 10 hours after the light pulse. We identified numerous genes that were downregulated by the light pulse 1 hour after the pulse relative to no pulse group. Intriguingly, many of these genes had a flipped pattern of expression 9 hours later - the pulse group had higher expression than the no pulse group. This pattern is consistent with the shifted phase of locomotor activity expected after the light pulse application. We also identified clock gene homologs in M. wittfeldae that had distinct expression patterns from other arthropods.

animal behavior and cognition↗

bioRxiv2025

Epithelial tumor cells utilize mast cell-derived histamine to regulate perineural invasion

Cancer dissemination by perineural invasion (PNI) is associated with poor outcomes in epithelial malignancies, yet the cellular interactions critical to this process are not fully defined. Single-cell transcriptomic analysis of cutaneous squamous cell carcinoma (cSCC) with PNI highlighted KITLG-KIT signaling activation between keratinocytes and mast cells. Additionally, we observed increased expression of HRH1 on tumor cells, which encodes the H1 histamine receptor. We confirmed these changes in other cancers, including PNI-positive hepatobiliary and oral mucosal tumors. Histamine enhanced tumor invasion into nerve in organoids that recapitulate key features of PNI, an effect rescued by H1-antihistamines. Mechanistically, broad upregulation of matrix metalloproteinases (MMPs) through P38 activation underscored histamine-mediated PNI by enabling collagen degradation in the nerve sheath. Examination of multiple cancer types with PNI showed co-expression of HRH1 and MMP2 on tumor cells as well as type IV collagen loss in involved nerves. Retrospective analysis of >15,000 patient health records in two independent databases demonstrated that H1-antihistamine use improved overall survival and immunotherapy response in cancers that spread by PNI. Together, these data reveal a critical role for mast cells in PNI and present a new therapeutic strategy for targeting this process in epithelial cancers.

cancer biology↗

bioRxiv2025

High-Throughput Multiomics Profiling of Model Systems Using the AVITI24 Platform

We present a multiomics platform comprising Teton, a detection assay system, and AVITI24, a dual-flowcell instrument that performs both cellular imaging and sequencing readout. Teton integrates a compartmentalized flowcell for cell culture with methods to measure morphology, RNA, and protein at subcellular resolution. The platform quantifies morphological features through cell painting of 6 cellular components, RNA expression of up to 350 transcripts via sequencing of oligonucleotides hybridized to mRNA, and protein expression of up to 200 targets using antibody-linked oligonucleotide sequencing. The flow cell accommodates >1 million cells in a 10 cm squared open-well format or can be subdivided into 12 or 48 wells to support experiments with multiple conditions or time points. We describe and validate the detection methods of the platform and showcase its capabilities by co-culturing three cancer cell lines and elucidating the cellular pathways triggered by various drug treatments as a function of time. Using multiple time points enables us to capture the dynamics of cellular processes including receptor activation and signaling cascades. The results demonstrate how different cancer cells evade TNF-induced apoptosis by activating compensatory signaling programs that maintain survival despite pro-apoptotic cues. Our model system replicates previously published results and highlights the versatility of the platform in enabling rapid, high-throughput analysis of complex cellular responses in varied biological contexts.

genomics↗

bioRxiv2025

A simplified hybrid capture approach retains high specificity and enables PCR-free workflow

Hybrid capture is a critical technology for selective enrichment of genomic regions of interest, enabling cost-effective focused sequencing in both clinical and research applications. We present a simplified hybrid capture approach that eliminates complexities typically associated with hybridization-based selection methods by directly loading the hybridization product onto the sequencing flow cell. The workflow removes bead-based steps, washes, and post-hybridization PCR, while retaining high capture specificity and library complexity. The approach is enabled by the development of a streptavidin flow cell surface, a method to circularize and amplify captured targets on the flow cell, and a fast hybridization protocol. We demonstrate application across targeted panel sizes and improvements to library complexity and variant calling. We also show how the approach can be used to create an entirely PCR-free targeted sequencing workflow that further improves variant calling and enables the detection of repeat expansions.

genomics↗

bioRxiv2024

Neural dynamics in the orbitofrontal cortex reveal cognitive strategies

While the orbitofrontal cortex (OFC) is implicated in learning and inferring latent states, the precise computation performed by OFC for state inference is unclear. Here we show that rat OFC updates beliefs about states, and this process is decipherable from OFC dynamics in rats performing state inference, but not alternative strategies. We trained rats to perform a temporal wagering task with hidden reward states. Well-trained rats used state inference when deciding how long to wait for rewards, and OFC inactivations impaired belief updating about states. Electrophysiology and novel population analysis methods identified latent neural factors reflecting inferred states in rats performing inference, but not other strategies. Neural firing rates and latent population factors showed abrupt changes following trials that were informative of state transitions. These results identify a precise computation performed by OFC, and reveal neural signatures of inference.

neuroscience↗

bioRxiv2024

Mesolimbic dopamine encodes reward prediction errors independent of learning rates

Biological accounts of reinforcement learning posit that dopamine encodes reward prediction errors (RPEs), which are multiplied by a learning rate to update state or action values. These values are thought to be represented in synaptic weights in the striatum, and updated by dopamine-dependent plasticity, suggesting that dopamine release might reflect the product of the learning rate and RPE. Here, we leveraged the fact that animals learn faster in volatile environments to characterize dopamine encoding of learning rates in the nucleus accumbens core (NAcc). We trained rats on a task with semi-observable states offering different rewards, and rats adjusted how quickly they initiated trials across states using RPEs. Computational modeling and behavioral analyses showed that learning rates were higher following state transitions, and scaled with trial-by-trial changes in beliefs about hidden states, approximating normative Bayesian strategies. Notably, dopamine release in the NAcc encoded RPEs independent of learning rates, suggesting that dopamine-independent mechanisms instantiate dynamic learning rates.

neuroscience↗

bioRxiv2023

Estrogenic control of reward prediction errors and reinforcement learning

Gonadal hormones act throughout the brain1, and neuropsychiatric disorders vary in symptom severity over the reproductive cycle, pregnancy, and perimenopause2-4. Yet how hormones influence cognitive processes is unclear. Exogenous 17{beta}-estradiol modulates dopamine signaling in the nucleus accumbens core (NAcc)5,6, which instantiates reward prediction errors (RPEs) for reinforcement learning7-16. Here we show that endogenous 17{beta}-estradiol enhances RPEs and sensitivity to previous rewards by reducing dopamine reuptake proteins in the NAcc. Rats performed a task with different reward states; they adjusted how quickly they initiated trials across states, balancing effort against expected rewards. NAcc dopamine reflected RPEs that predicted and causally influenced initiation times. Elevated endogenous 17{beta}-estradiol increased sensitivity to reward states by enhancing dopaminergic RPEs in the NAcc. Proteomics revealed reduced dopamine transporter expression. Finally, knockdown of midbrain estrogen receptors suppressed reinforcement learning. 17{beta}-estradiol therefore controls RPEs via dopamine reuptake, mechanistically revealing how hormones influence neural dynamics for motivation and learning.

neuroscience↗

bioRxiv2023

Rats rapidly switch between retrospective and inferential value computations

The value of the environment determines animals motivational states and sets expectations for error-based learning1-3. How are values computed? Rein-forcement learning systems can store or "cache" values of states or actions that are learned from experience, or they can compute values using a model of the environment to simulate possible futures3. These value computations have distinct trade-offs, and a central question is how neural systems decide which computations to use or whether/how to combine them4-8. Here we show that rats use distinct value computations for sequential decisions within single tri-als. We used high-throughput training to collect statistically powerful datasets from 291 rats performing a temporal wagering task with hidden reward states. Rats adjusted how quickly they initiated trials and how long they waited for re-wards across states, balancing effort and time costs against expected rewards. Statistical modeling revealed that animals computed the value of the environ-ment differently when initiating trials versus when deciding how long to wait for rewards, even though these decisions were only seconds apart. Moreover, value estimates interacted via a dynamic learning rate. Our results reveal how distinct value computations interact on rapid timescales, and demonstrate the power of using high-throughput training to understand rich, cognitive behav-iors.

neuroscience↗

bioRxiv2022

Experimental evolution in TP53 deficient gastric organoids recapitulates tumorigenesis

The earliest events during human tumor initiation, while poorly characterized, may hold clues to malignancy detection and prevention1. Here we model occult pre-neoplasia by bi-allelically inactivating TP53, a common early event in gastric cancer, in human gastric organoids. Causal relationships between this initiating genetic lesion and resulting phenotypes were established using experimental evolution in multiple clonally derived cultures over two years. TP53 loss elicited progressive aneuploidy, including copy number alterations and structural variants prevalent in gastric cancers, with evident preferred orders. Longitudinal single cell sequencing of TP53 deficient gastric organoids similarly indicates progression towards malignant transcriptional programs. Moreover, high-throughput lineage tracing with expressed cellular barcodes demonstrates reproducible dynamics whereby initially rare subclones with shared transcriptional programs repeatedly attain clonal dominance. This powerful platform for experimental evolution exposes stringent selection, clonal interference, and a striking degree of phenotypic convergence in pre-malignant epithelial organoids. These data imply predictability in the earliest stages of tumorigenesis and reveal evolutionary constraints and barriers to malignant transformation with implications for earlier detection and interception of aggressive, genome instable tumors.

cancer biology↗

bioRxiv2022

RET activation controlled by MAB21L4-CacyBP interaction drives squamous cell carcinoma

Epithelial squamous cell carcinomas (SCC) most commonly originate in the skin, where they display disruptions in the normally tightly regulated homeostatic balance between keratinocyte proliferation and terminal differentiation. We performed a transcriptome-wide screen for genes of unknown function that possess inverse expression patterns in differentiating keratinocytes compared to cutaneous SCC (cSCC) and identified MAB21L4 (C2ORF54) as an enforcer of terminal differentiation that suppresses carcinogenesis. Loss of MAB21L4 in human cSCC organoids enabled malignant transformation through increased expression of the receptor tyrosine kinase rearranged during transfection (RET). In addition to transcriptional upregulation of RET, MAB21L4 deletion preempted recruitment of the CacyBP-Siah1 E3 ligase complex to RET and reduced its ubiquitylation. Both genetic disruption of RET or selective RET inhibition with BLU-667 (pralsetinib) suppressed tumorigenesis in SCC organoids and in vivo tumors while inducing concomitant differentiation. Our results suggest that targeting RET activation is a potential therapeutic strategy for treating SCC. Statement of SignificanceFew targeted therapies are available to individuals with cSCC who seek or require non-surgical management. Our study demonstrates that downregulation of RET is required for epithelial differentiation and opposes carcinogenesis in cSCC as well as SCC arising from other epithelial tissues.

cancer biology↗

bioRxiv2018

Time efficient preparation methods for MRI brain scanning in awake young children and factors associated with success

ObjectiveYoung children are often unable to remain still for magnetic resonance imaging (MRI). Various preparation methods have been reported to avoid sedation or anesthesia, with mixed success rates and feasibility. Here we describe a time-efficient preparation method and factors associated with successful scanning in young chdilren.\n\nWe recruited 134 children aged 2.0-5.0 years for an MRI study. Some children completed a training session on a mock scanner, and all children received a 15-20 minute introduction to scanning procedures immediately before their scan. We compared success between children receiving mock scanner training or not, and evaluated demographic or cognitive factors that predicted success.\n\nResults97 children (72%) completed at least one sequence successfully; 64 children provided high-quality data for all 3 sequences. Cognitive scores were higher in successful children, but children who received mock scanner training were less likely to be successful. A case-controlled comparison of children matched on age, gender, and cognitive scores found no differences between children receiving training or not.\n\nWe present a quick method for preparing young children for awake MRI scans. Our data suggests limited advantages of mock scanner preparation for healthy young children, and that cognitive abilities may help predict success.

neuroscience↗