Biology subjects

Clark, K.

Publications and source records attributed to Clark, K..

31 records · Page 2Linked to original sources

bioRxiv2022

The faculty-to-faculty mentorship experience: a survey on challenges and recommendations for improvements

Faculty at research institutions play a central role in advancing knowledge and careers, as well as promoting the well-being of students and colleagues in research environments. Faculty members must balance a host of activities - such as performing research, teaching, sourcing funds, administrative and service duties - with their roles as educators and mentors. Mentorship from experienced peers has been touted as critical for enabling these myriad roles to allow faculty development, career progression, and satisfaction. However, there is little information available on who supports faculty and best ways to structure a faculty mentorship program for early- and mid-career academics. Furthermore, the extent to which mentorship and mentoring programs have been offered to faculty members has not been widely characterized. It is also unclear what challenges faculty receiving mentorship may face and which aspects could be further improved. In the interest of advocating for increased and enhanced faculty mentoring and mentoring programs, we surveyed faculty (i.e., group leaders) around the world to gather data on whether and how they receive mentoring from peers, senior researchers, informal mentoring programs, or formal mentoring programs at their institutions. We received responses from 457 early- and mid-career faculty and found that a substantial portion of respondents either reported having no mentor or a lack of a formal mentoring scheme. Qualitative responses on the quality of mentorship revealed that the most common complaints regarding mentorship included lack of mentor availability, unsatisfactory commitment to mentorship, and non-specific or non-actionable advice. Our findings further identified key mentorship elements desired by faculty mentees. Based on these suggestions, we identify a need for training for faculty mentors as well as strategies for individual mentors, departments, and institutions for funding and design of more intentional and supportive mentorship programs for early- and mid-career faculty.

scientific communication and education↗

bioRxiv2022

Data Descriptor: Human whole exome genotype data for Alzheimer's Disease

Bigger sample size can help to identify new genetic variants contributing to an increased risk of developing Alzheimers disease. However, the heterogeneity of the whole-exome sequencing (WES) data generation methods presents a challenge to a joint analysis. Here we present a bioinformatics strategy for joint calling 20,504 WES samples collected across nine studies and sequenced using ten different capture kits in fourteen sequencing centers in the Alzheimers Disease Sequencing Project. gVCFs of samples were joint-called by the Genome Center for Alzheimers Disease into a single VCF, containing only positions within the union of capture kits. The VCF was then processed using specific strategies to account for the batch effects arising from the use of different capture kits from different studies. We identified 8.2 million autosomal variants. 96.82% of the variants are high-quality, and are located in 28,579 Ensembl transcripts. 41% of the variants are intronic and 15% are missense variants. 1.8% of the variants are with CADD>30. Our new strategy for processing these diversely generated WES samples has shown to generate high-quality data. The improved ability to combine data sequenced in different batches benefits the whole genomics research community. The WES data are accessible to the scientific community via https://dss.niagads.org/.

genetics↗

bioRxiv2022

A phenotype-based forward genetic screen identifies Dnajb6 as a sick sinus syndrome gene

Sick sinus syndrome (SSS) is a group of heart rhythm disorders caused by malfunction of the sinus node, the hearts primary pacemaker. Partially owing to its aging-associated phenotypic manifestation and low expressivity, molecular mechanisms of SSS remain difficult to decipher. Here, we aim to develop a phenotype-based forward genetic approach in the zebrafish (Danio rerio) animal model for discovering essential genes which dysfunction could result in SSS-like phenotypes. Previously we showed the generation of protein trap library by using a revertible gene-breaking transposon (GBT)-based insertional mutagenesis system. Here, we reported the generation of a collection of 35 zebrafish insertional cardiac lines derived from this protein trap library, which was screened using electrocardiographic measurements. As a result, three mutants with SSS-like phenotypes were identified. We then focused on one of these 3 GBT mutants called GBT411 in which dnajb6b gene was disrupted, and conducted expressional, genetic, transcriptome, and electrophysiological studies using both zebrafish and mouse models. These studies confirmed the identity of Dnajb6 as a novel SSS causative gene with a unique expression pattern within the specialized population of sinus node pacemaker cardiomyocytes that lack the expression of HCN4 channels. Together, this study demonstrates the feasibility of a genetic screening approach in an adult vertebrate animal model for discovering new genetic factors for a heart rhythm disorder such as SSS.

genetics↗

bioRxiv2021

Light-regulated SIK1 remodels the synaptic phosphoproteome to induce sleep

The sleep and circadian systems act in concert to regulate sleep-wake timing, yet the molecular mechanisms that underpin their interaction to induce sleep remain unknown. Synaptic protein phosphorylation, driven by the kinase SIK3, correlates with sleep pressure, however it is unclear whether these phosphoproteome changes are causally responsible for inducing sleep. Here we show that the light-dependent activity of SIK1 controls the phosphorylation of a subset of the brain phosphoproteome to induce sleep in a manner that is independent of sleep pressure. By uncoupling phosphorylation and sleep induction from sleep pressure, we establish that synaptic protein phosphorylation provides a causal mechanism for the induction of sleep under different environmental contexts. Furthermore, we propose a framework that details how the salt-inducible kinases regulate the synaptic phosphoproteome to integrate exogenous and endogenous stimuli, thereby providing the molecular basis upon which the sleep and circadian systems interact to control the sleep-wake cycle.

neuroscience↗

bioRxiv2021

Tensin3 interaction with talin drives formationof fibronectin-associated fibrillar adhesions

The formation of healthy tissue involves continuous remodelling of the extracellular matrix (ECM). Whilst it is known that this requires integrin-associated cell-ECM adhesion sites (CMAs) and actomyosin-mediated forces, the underlying mechanisms remain unclear. Here we examine how tensin3 contributes to formation of fibrillar adhesions (FBs) and fibronectin fibrillo-genesis. Using BioID mass spectrometry and a mitochondrial targeting assay, we establish that tensin3 associates with the mechanosensors talin and vinculin. We show that the talin R11 rod domain binds directly to a helical motif within the central intrinsically disordered region (IDR) of tensin3, whilst vinculin binds indirectly to tensin3 via talin. Using CRISPR knock-out cells in combination with defined tensin3 mutations, we show (i) that tensin3 is critical for formation of 5{beta}1-integrin FBs and for fibronectin fibrillogenesis, and (ii) the talin/tensin3 interaction drives this process, with vinculin acting to potentiate it.

cell biology↗

bioRxiv2021

Chimeric RNA:DNA Donorguide Improves HDR in vitro and in vivo

Introducing small genetic changes to study specific mutations or reverting clinical mutations to wild type has been an area of interest in precision genomics for several years. In fact, it has been found that nearly 90% of all human pathogenic mutations are caused by small genetic variations, and the methods to efficiently and precisely correct these errors are critically important. One common way to make these small DNA changes is to provide a single stranded DNA (ssDNA) donor containing the desired alteration together with a targeted double-strand break (DSB) at the genomic target. The donor is typically flanked by regions of homology that are often ~30-100bp in length to leverage the homology directed repair (HDR) pathway. Coupling a ssDNA donor with a CRISPR-Cas9 to produce a targeted DSB is one of the most streamlined approaches to introduce small changes. However, in many cell types this approach results in a low rate of incorporation of the desired alteration and has undesired imprecise repair at the 5 or 3 junction due to artifacts of the DNA repair process. We herein report a technology that couples the spatial temporal localization of an ssDNA repair template and leverages the nucleic acid components of the CRISPR-Cas9 system. We show that by direct fusion of an ssDNA template to the trans activating RNA (tracrRNA) to generate an RNA-DNA chimera, termed Donorguide, we recover precise integration of genetic alterations, with both increased integration rates and decreased imprecision at the 5 or 3 junctions relative to an ssODN donor in vitro in HEK293T cells as well as in vivo in zebrafish. Further, we show that this technology can be used to enhance gene conversion with other gene editing tools such as TALENs.

genetics↗

bioRxiv2020

Multi-Modal Biomarkers of Cerebral Edema in Low Resolution MRI

A central challenge of medical imaging studies is to extract biomarkers that characterize disease pathology or outcomes. Modern automated approaches have found tremendous success in high-resolution, high-quality magnetic resonance images (MRI). These methods, however, may not translate to low resolution images acquired on MRI scanners with lower magnetic field strength. In low-resource settings where low-field scanners are more common and there is a shortage of radiologists to manually interpret MRI scans, it is critical to develop automated methods that can augment or replace manual interpretation, while accommodating reduced image quality. We present a fully automated framework for translating radiological diagnostic criteria into image-based biomarkers, inspired by a project in which children with cerebral malaria were imaged using low-field 0.35 Tesla MRI. We integrate multi-atlas label fusion, which leverages high-resolution images from another sample as prior spatial information, with parametric Gaussian hidden Markov models based on image intensities, to create a robust method for determining ventricular cerebrospinal fluid volume. We also propose normalized image intensity and texture measurements to determine the loss of gray-to-white matter tissue differentiation and sulcal effacement. These integrated biomarkers have excellent classification performance for determining severe brain swelling due to cerebral malaria.

neuroscience↗

bioRxiv2020

Fully Automated Detection of Paramagnetic Rims in Multiple Sclerosis Lesions on 3T Susceptibility-Based MR Imaging

Background and PurposeThe presence of a paramagnetic rim around a white matter lesion has recently been shown to be a hallmark of a particular pathological type of multiple sclerosis (MS) lesion. Increased prevalence of these paramagnetic rim lesions (PRLs) is associated with a more severe disease course in MS. The identification of these lesions is time-consuming to perform manually. We present a method to automatically detect PRLs on 3T T2*-phase images. MethodsT1-weighted, T2-FLAIR, and T2*-phase MRI of the brain were collected at 3T for 19 subjects with MS. The images were then processed with lesion segmentation, lesion center detection, lesion labelling, and lesion-level radiomic feature extraction. A total of 877 lesions were identified, 118 (13%) of which contained a paramagnetic rim. We divided our data into a training set (15 patients, 673 lesions) and a testing set (4 patients, 204 lesions). We fit a random forest classification model on the training set and assessed our ability to classify lesions as PRL on the test set. ResultsThe number of PRLs per subject identified via our automated lesion labelling method was highly correlated with the gold standard count of PRLs per subject, r = 0.91 (95% CI [0.79, 0.97]). The classification algorithm using radiomic features can classify a lesion as PRL or not with an area under the curve of 0.80 (95% CI [0.67, 0.86]). ConclusionThis study develops a fully automated technique for the detection of paramagnetic rim lesions using standard T1 and FLAIR sequences and a T2*phase sequence obtained on 3T MR images. HighlightsO_LIA fully automated method for both the identification and classification of paramagnetic rim lesions is proposed. C_LIO_LIRadiomic features in conjunction with machine learning algorithms can accurately classify paramagnetic rim lesions. C_LIO_LIChallenges for classification are largely driven by heterogeneity between lesions, including equivocal rim signatures and lesion location. C_LI

neuroscience↗

bioRxiv2020

Characterization of gene repression by designed transcription activator-like effector dimer proteins

Gene regulation by control of transcription initiation is a fundamental property of living cells. Much of our understanding of gene repression originated from studies of the E. coli lac operon switch, where DNA looping plays an essential role. To validate and generalize principles from lac for practical applications, we previously described artificial DNA looping driven by designed Transcription Activator-Like Effector Dimer (TALED) proteins. Because TALE monomers bind the idealized symmetrical lac operator sequence in two orientations, our prior studies detected repression due to multiple DNA loops. We now quantitatively characterize gene repression in living E. coli by a collection of individual TALED loops with systematic loop length variation. Fitting of a thermodynamic model allows unequivocal demonstration of looping and comparison of the engineered TALED repression system with the natural lac repressor system. Statement of SignificanceWe are designing and testing in living bacteria artificial DNA looping proteins engineered based on principles learned from studies of the E. coli lac repressor. The engineered proteins are based on artificial dimers of Transcription Activator-Like Effector (TALE) proteins that have programmable DNA binding specificities. The current work is the first to create unique DNA repression loops using this approach. Systematic study of repression as a function of loop size, with data fitting to a thermodynamic model, now allows this system to be compared in detail with lac repressor loops, and relevant biophysical parameters to be estimated. This approach has implications for the artificial regulation of gene expression.

biophysics↗

bioRxiv2020

Ancestral absence of electron transport chains in Patescibacteria and DPANN

Recent discoveries suggest that the candidate superphyla Patescibacteria and DPANN constitute a large fraction of the phylogenetic diversity of Bacteria and Archaea. Their small genomes and limited coding potential have been hypothesized to be ancestral adaptations to obligate symbiotic lifestyles. To test this hypothesis, we performed cell-cell association, genomic, and phylogenetic analyses on 4,829 individual cells of Bacteria and Archaea from 46 globally distributed surface and subsurface field samples. This confirmed the ubiquity and abundance of Patescibacteria and DPANN in subsurface environments, the small size of their genomes and cells, and the divergence of their gene content from other Bacteria and Archaea. Our analyses suggest that most Patescibacteria and DPANN in the studied subsurface environments do not form specific physical associations with other microorganisms. These data also suggest that their unusual genomic features and prevalent auxotrophies may be a result of minimal cellular energy transduction mechanisms that potentially precede the evolution of respiration, thus relying solely on fermentation for energy conservation.

evolutionary biology↗

bioRxiv2018

Disruption of IRE1α through its Kinase Domain Attenuates Multiple Myeloma

Multiple myeloma (MM) arises from malignant immunoglobulin-secreting plasma cells and remains an incurable, often lethal disease despite recent therapeutic advances. The unfolded-protein response sensor IRE1 supports protein secretion by deploying a kinase-endoribonuclease module to activate the transcription factor XBP1s. MM cells may coopt the IRE1-XBP1s pathway; however, the validity of IRE1 as a potential MM therapeutic target is controversial. Here we show that genetic disruption of IRE1 or XBP1s, or pharmacologic IRE1 kinase inhibition, attenuated subcutaneous or orthometastatic growth of MM tumors in mice, and augmented efficacy of two well-established frontline antimyeloma agents, bortezomib or lenalidomide. Mechanistically, IRE1 perturbation inhibited expression of key components of the ER-associated degradation machinery, as well as cytokines and chemokines known to promote MM growth. Selective IRE1 kinase inhibition reduced viability of CD138+ plasma cells while sparing CD138- cells from bone marrow of newly diagnosed MM patients or patients whose disease relapsed after 1 - 4 lines of treatment in both US- and EU-based cohorts. IRE1 inhibition preserved survival and glucose-induced insulin secretion by pancreatic microislets. Together, these results establish a strong therapeutic rationale for targeting IRE1 with kinase-based small-molecule inhibitors in MM.\n\nSignificance statementMultiple myeloma (MM) is a lethal malignancy of plasma cells. MM cells have an expanded endoplasmic reticulum (ER) that is constantly under stress due to immunoglobulin hyperproduction. The ER-resident sensor IRE1 mitigates ER stress by expanding the ERs protein-folding capacity while supporting proteasomal degradation of misfolded ER proteins. IRE1 elaborates these functions by deploying its cytoplasmic kinase-RNase module to activate the transcription factor XBP1s. The validity of IRE1 as a potential therapeutic target in MM has been questioned. Using genetic and pharmacologic disruption in vitro and in vivo, we demonstrate that the IRE1-XBP1s pathway plays a critical role in MM growth. We further show that IRE1s kinase domain is an effective and safe potential small-molecule target for MM therapy.

cancer biology↗

bioRxiv2018

Inducing controlled cell cycle arrest and re-entry during asexual proliferation of Plasmodium falciparum malaria parasites.

The life cycle of the malaria parasite Plasmodium falciparum is tightly regulated, oscillating between stages of intense proliferation and quiescence. Cyclic 48-hour asexual replication of Plasmodium is markedly different from cell division in higher eukaryotes, and mechanistically poorly understood. Here, we report tight synchronisation of malaria parasites during the early phases of the cell cycle by exposure to DL--difluoromethylornithine (DFMO), which results in the depletion of polyamines. This induces an inescapable cell cycle arrest in G1 (~15 hours post-invasion) by blocking G1/S transition. Cell cycle-arrested parasites enter a quiescent G0-like state but, upon addition of exogenous polyamines, re-initiate their cell cycle in a coordinated fashion. This ability to halt malaria parasites at a specific point in their cell cycle, and to subsequently trigger re-entry into the cell cycle, provides a valuable framework to investigate cell cycle regulation in these parasites. We therefore used gene expression analyses to show that re-entry into the cell cycle involves expression of Ca2+-sensitive (cdpk4 and pk2) and mitotic kinases (nima and ark2), with deregulation of the pre-replicative complex associated with expression of pk2. Changes in gene expression could be driven through transcription factors MYB1 and two ApiAP2 family members. This new approach to parasite synchronisation therefore expands our currently limited toolkit to investigate cell cycle regulation in malaria parasites.

cell biology↗

bioRxiv2018

BDQC: a general-purpose analytics tool for domain-blind validation of Big Data

Translational biomedical research is generating exponentially more data: thousands of whole-genome sequences (WGS) are now available; brain data are doubling every two years. Analyses of Big Data, including imaging, genomic, phenotypic, and clinical data, present qualitatively new challenges as well as opportunities. Among the challenges is a proliferation in ways analyses can fail, due largely to the increasing length and complexity of processing pipelines. Anomalies in input data, runtime resource exhaustion or node failure in a distributed computation can all cause pipeline hiccups that are not necessarily obvious in the output. Flaws that can taint results may persist undetected in complex pipelines, a danger amplified by the fact that research is often concurrent with the development of the software on which it depends. On the positive side, the huge sample sizes increase statistical power, which in turn can shed new insight and motivate innovative analytic approaches. We have developed a framework for Big Data Quality Control (BDQC) including an extensible set of heuristic and statistical analyses that identify deviations in data without regard to its meaning (domain-blind analyses). BDQC takes advantage of large sample sizes to classify the samples, estimate distributions and identify outliers. Such outliers may be symptoms of technology failure (e.g., truncated output of one step of a pipeline for a single genome) or may reveal unsuspected \" signal\" in the data (e.g., evidence of aneuploidy in a genome). We have applied the framework to validate real-world WGS analysis pipelines. BDQC successfully identified data outliers representing various failure classes, including genome analyses missing a whole chromosome or part thereof, hidden among thousands of intermediary output files. These failures could then be resolved by reanalyzing the affected samples. BDQC both identified hidden flaws as well as yielded new insights into the data. BDQC is designed to complement quality software development practices. There are multiple benefits from the application of BDQC at all pipeline stages. By verifying input correctness, it can help avoid expensive computations on flawed data. Analysis of intermediary and final results facilitates recovery from aberrant termination of processes. All these computationally inexpensive verifications reduce cryptic analytical artifacts that could seriously preclude clinical-grade genome interpretation. BDQC is available at https://github.com/ini-bdds/bdqc.

bioinformatics↗