Functional genetics reveals modulators of anti-microtubule drug sensitivity.

Microtubules play essential roles in diverse cellular processes and are important pharmacological targets for treating human disease. Here, we sought to identify cellular factors that modulate the sensitivity of cells to anti-microtubule drugs. We conducted a genome-wide CRISPR/Cas9-based functional genetics screen in human cells treated with the microtubule-destabilizing drug nocodazole or the microtubule-stabilizing drug taxol. We further conducted a focused secondary screen to test drug sensitivity for ~1400 gene targets across two distinct human cell lines and to additionally test sensitivity to the Kif11-inhibitor, STLC. These screens defined gene targets whose loss enhances or suppresses sensitivity to anti-microtubule drugs. In addition to gene targets whose loss sensitized cells to multiple compounds, we observed cases of differential sensitivity to specific compounds and differing requirements between cell lines. Our downstream molecular analysis further revealed additional roles for established microtubule-associated proteins and identified new players in microtubule function.

Model-based iterative reconstruction for direct imaging with point spread function encoded echo planar MRI.

BACKGROUND: Echo planar imaging (EPI) is a fast measurement technique commonly used in magnetic resonance imaging (MRI), but is highly sensitive to measurement non-idealities in reconstruction. Point spread function (PSF)-encoded EPI is a multi-shot strategy which alleviates distortion, but acquisition of encodings suitable for direct distortion-free imaging prolongs scan time. In this work, a model-based iterative reconstruction (MBIR) framework is introduced for direct imaging with PSF-EPI to improve image quality and acceleration potential. METHODS: An MBIR platform was developed for accelerated PSF-EPI. The reconstruction utilizes a subspace representation, is regularized to promote local low-rankedness (LLR), and uses variable splitting for efficient iteration. Comparisons were made against standard reconstructions from prospectively accelerated PSF-EPI data and with retrospective subsampling. Exploring aggressive partial Fourier acceleration of the PSF-encoding dimension, additional comparisons were made against an extension of Homodyne to direct PSF-EPI in numerical experiments. A neuroradiologists' assessment was completed comparing images reconstructed with MBIR from retrospectively truncated data directly against images obtained with standard reconstructions from non-truncated datasets. RESULTS: Image quality results were consistently superior for MBIR relative to standard and Homodyne reconstructions. As the MBIR signal model and reconstruction allow for arbitrary sampling of the PSF space, random sampling of the PSF-encoding dimension was also demonstrated, with quantitative assessments indicating best performance achieved through nonuniform PSF sampling combined with partial Fourier. With retrospective subsampling, MBIR reconstructs high-quality images from sub-minute scan datasets. MBIR was shown to be superior in a neuroradiologists' assessment with respect to three of five performance criteria, with equivalence for the remaining two. CONCLUSIONS: A novel image reconstruction framework is introduced for direct imaging with PSF-EPI, enabling arbitrary PSF space sampling and reconstruction of diagnostic-quality images from highly accelerated PSF-encoded EPI data.

Transkingdom Network Analysis (TkNA): a systems framework for inferring causal factors underlying host-microbiota and other multi-omic interactions.

We present Transkingdom Network Analysis (TkNA), a unique causal-inference analytical framework that offers a holistic view of biological systems by integrating data from multiple cohorts and diverse omics types. TkNA helps to decipher key players and mechanisms governing host-microbiota (or any multi-omic data) interactions in specific conditions or diseases. TkNA reconstructs a network that represents a statistical model capturing the complex relationships between different omics in the biological system. It identifies robust and reproducible patterns of fold change direction and correlation sign across several cohorts to select differential features and their per-group correlations. The framework then uses causality-sensitive metrics, statistical thresholds and topological criteria to determine the final edges forming the transkingdom network. With the subsequent network's topological features, TkNA identifies nodes controlling a given subnetwork or governing communication between kingdoms and/or subnetworks. The computational time for the millions of correlations necessary for network reconstruction in TkNA typically takes only a few minutes, varying with the study design. Unlike most other multi-omics approaches that find only associations, TkNA focuses on establishing causality while accounting for the complex structure of multi-omic data. It achieves this without requiring huge sample sizes. Moreover, the TkNA protocol is user friendly, requiring minimal installation and basic familiarity with Unix. Researchers can access the TkNA software at https://github.com/CAnBioNet/TkNA/ .

Locally Low-Rank Denoising of Multi-Echo Functional MRI Data With Application in Resting-State Analysis.

OBJECTIVES: Locally low-rank (LLR) denoising of functional magnetic resonance imaging (fMRI) time series image data is extended to multi-echo (ME) data. The proposed method extends the capabilities of non-physiologic noise suppression beyond single-echo applications with a dedicated ME algorithm. MATERIALS AND METHODS: Following an institutional review board (IRB) approved protocol, resting-state fMRI data were acquired in 7 healthy subjects. A compact 3T scanner enabled whole-brain acquisition of multiband ME fMRI data at high spatial resolution (1.4 × 1.4 × 2.8 mm 3 ) with a 1810 ms repetition time (TR). Image data were denoised with ME-LLR preceding functional processing. The results of connectivity maps generated from denoised data were compared with maps generated with equivalent processing of non-denoised images. To assess ME-LLR as a method to reduce scan time, comparisons were made between maps computed from image data with full and retrospectively truncated durations. Assessments were completed with seed-based connectivity analyses using echo-combined image data. In a feasibility assessment, nondenoised and denoised full-duration echo-combined data were equivalently processed with independent component analysis (ICA) and compared. RESULTS: ME-LLR denoising yielded strengthened resting-state network connectivity maps after nuisance regression and seed-based connectivity analysis. In assessing ME-LLR as a scan reduction mechanism, maps generated from denoised data at half scan time showed comparable quality with maps generated from full-duration, non-denoised data, at both single subject and group levels. ME-LLR substantially increased temporal signal-to-noise ratio (tSNR) for image data respective to each individual echo and for image data after nuisance regression. Among echo-specific image volumes, increases in tSNR yielded by ME-LLR were most pronounced for image data with the longest echo time and thereby lowest SNR. ICA showed resting-state networks consistently identified between non-denoised and denoised data, with clearer demarcation of networks for ME-LLR. CONCLUSIONS: ME-LLR is demonstrated to suppress non-physiologic noise, enhance functional connectivity map quality, and could potentially facilitate scan time reduction in ME-fMRI.

Multi-omic network analysis identified betacellulin as a novel target of omega-3 fatty acid attenuation of western diet-induced nonalcoholic steatohepatitis.

Clinical and preclinical studies established that supplementing diets with ω3 polyunsaturated fatty acids (PUFA) can reduce hepatic dysfunction in nonalcoholic steatohepatitis (NASH) but molecular underpinnings of this action were elusive. Herein, we used multi-omic network analysis that unveiled critical molecular pathways involved in ω3 PUFA effects in a preclinical mouse model of western diet induced NASH. Since NASH is a precursor of liver cancer, we also performed meta-analysis of human liver cancer transcriptomes that uncovered betacellulin as a key EGFR-binding protein upregulated in liver cancer and downregulated by ω3 PUFAs in animals and humans with NASH. We then confirmed that betacellulin acts by promoting proliferation of quiescent hepatic stellate cells, inducing transforming growth factor-ß2 and increasing collagen production. When used in combination with TLR2/4 agonists, betacellulin upregulated integrins in macrophages thereby potentiating inflammation and fibrosis. Taken together, our results suggest that suppression of betacellulin is one of the key mechanisms associated with anti-inflammatory and anti-fibrotic effects of ω3 PUFA on NASH.

A phosphatidylinositol phosphate kinase inhibits Ras activation and regulates chemorepulsion in Dictyostelium discoideum.

During developmental and immune responses, cells move towards or away from some signals. Although much is known about chemoattraction, chemorepulsion (the movement of cells away from a stimulus) remains poorly understood. Proliferating Dictyostelium discoideum cells secrete a chemorepellent protein called AprA. Examining existing knockout strains, we previously identified proteins required for AprA-induced chemorepulsion, and a genetic screen suggested that the enzyme phosphatidylinositol phosphate kinase A (PIPkinA, also known as Pik6) might also be needed for chemorepulsion. Here, we show that cells lacking PIPkinA are not repelled by AprA, and that this phenotype is rescued by expression of PIPkinA. To bias cell movement, AprA inhibits Ras activation at the side of the cell closest to the source of AprA, and we find that PIPkinA is required for AprA to inhibit Ras activation. PIPkinA decreases levels of phosphatidylinositol 4-phosphate [PI(4)P] and phosphatidylinositol (3,4,5)-trisphosphate [PI(3,4,5)P3], and possibly because of these effects, potentiates phagocytosis and inhibits cell proliferation. Cells lacking PIPkinA show normal AprA binding, suggesting that PIPkinA regulates chemorepulsion at a step between the AprA receptor and AprA inhibition of Ras activation.

Improved Resting-State Functional MRI Using Multi-Echo Echo-Planar Imaging on a Compact 3T MRI Scanner with High-Performance Gradients.

In blood-oxygen-level-dependent (BOLD)-based resting-state functional (RS-fMRI) studies, usage of multi-echo echo-planar-imaging (ME-EPI) is limited due to unacceptable late echo times when high spatial resolution is used. Equipped with high-performance gradients, the compact 3T MRI system (C3T) enables a three-echo whole-brain ME-EPI protocol with smaller than 2.5 mm isotropic voxel and shorter than 1 s repetition time, as required in landmark fMRI studies. The performance of the ME-EPI was comprehensively evaluated with signal variance reduction and region-of-interest-, seed- and independent-component-analysis-based functional connectivity analyses and compared with a counterpart of single-echo EPI with the shortest TR possible. Through the multi-echo combination, the thermal noise level is reduced. Functional connectivity, as well as signal intensity, are recovered in the medial orbital sulcus and anterior transverse collateral sulcus in ME-EPI. It is demonstrated that ME-EPI provides superior sensitivity and accuracy for detecting functional connectivity and/or brain networks in comparison with single-echo EPI. In conclusion, the high-performance gradient enabled high-spatial-temporal resolution ME-EPI would be the method of choice for RS-fMRI study on the C3T.

Technical note: Improved differentiation of calcification from hemosiderin using paramagnetic- and diamagnetic-specific magnetic resonance susceptibility weighted imaging (p-SWI, d-SWI).

INTRODUCTION: Differentiation of calcification and calcium-containing tissue from blood products remains challenging using magnetic resonance imaging (MRI). We developed a novel post-processing algorithm which creates both paramagnetic- and diamagnetic-specific SWI images generated from T2* weighted images using distinct "positive" and "negative" phase masks. METHODS: 10 patients who had undergone clinical MRI scanning of the brain with a rapid echo planar based T2*-weighted EPI-GRE pulse sequence with evidence for either hemosiderin and/or calcifications were retrospectively identified. Complex raw k-space data from individual imaging coils were then extracted, reconstructed, and appropriately combined to produce magnitude and phase images using a phase preserving method. The final reconstructed images included the T2* EPI-GRE magnitude images, p-SWI and d-SWI images. Filtered phase images were also available for review. Correlation with CT scans and MR imaging appearance over time corroborated the composition of the voxels. RESULTS: Differential "blooming" of diamagnetic and paramagnetic foci was readily identified on the corresponding p-SWI and d-SWI images and provided fast and reliable visual differentiation of diamagnetic from paramagnetic susceptibility effects by ascertaining which of the two images depicted the greatest "blooming" effect. Correlation with the available filtered phase maps was not necessary for differentiation of paramagnetic from diamagnetic image components. CONCLUSION: Clinical interpretation of SWI images can be further enhanced by creating specific p-SWI and d-SWI image pairs which contain greater visual information than the combination of standard p-SWI images and phase image.

Transkingdom Network Analysis (TkNA): a systems framework for inferring causal factors underlying host-microbiota and other multi-omic interactions.

Technological advances have generated tremendous amounts of high-throughput omics data. Integrating data from multiple cohorts and diverse omics types from new and previously published studies can offer a holistic view of a biological system and aid in deciphering its critical players and key mechanisms. In this protocol, we describe how to use Transkingdom Network Analysis (TkNA), a unique causal-inference analytical framework that can perform meta-analysis of cohorts and detect master regulators among measured parameters that govern pathological or physiological responses of host-microbiota (or any multi-omic data) interactions in a particular condition or disease. TkNA first reconstructs the network that represents a statistical model capturing the complex relationships between the different omics of the biological system. Here, it selects differential features and their per-group correlations by identifying robust and reproducible patterns of fold change direction and sign of correlation across several cohorts. Next, a causality-sensitive metric, statistical thresholds, and a set of topological criteria are used to select the final edges that form the transkingdom network. The second part of the analysis involves interrogating the network. Using the network's local and global topology metrics, it detects nodes that are responsible for control of given subnetwork or control of communication between kingdoms and/or subnetworks. The underlying basis of the TkNA approach involves fundamental principles including laws of causality, graph theory and information theory. Hence, TkNA can be used for causal inference via network analysis of any host and/or microbiota multi-omics data. This quick and easy-to-run protocol requires very basic familiarity with the Unix command-line environment.

Neuropathologic changes associated with stereoelectroencephalography depth electrode placement.

BACKGROUND: The aim of this study was to detail the neuropathologic changes resulting from the surgical placement of stereoelectroencephalography (SEEG) leads in an initial small group of epilepsy cases and to raise awareness of this iatrogenic pathology, especially to those medical providers who specialize in the care of epilepsy patients. METHODS: Five consecutive patients who underwent epilepsy resection surgery following SEEG monitoring at OSF Saint Francis Medical Center were included in our report. Resection specimens were examined grossly and entirely submitted for microscopic evaluation by a neuropathologist. Seizure-related pathologies, as well as histologic changes related to SEEG electrode placement, were documented. RESULTS: The patient cohort included two females and three males, with an age range of 9 to 47 years. Neuropathologic examination revealed one or more seizure-related pathologies in each patient's resection specimen. In addition, all brain resection specimens showed multiple microinfarcts, which appeared to correlate with the placement and size of SEEG electrodes. Patchy leptomeningeal chronic inflammation was also seen in most cases. CONCLUSIONS: SEEG electrode placement is an effective procedure for determining epileptogenic regions and guiding subsequent resection surgeries in medically refractory epilepsy. Multiple microinfarcts and chronic inflammation are commonly seen in brain resection specimens following SEEG electrode insertion, but studies detailing these iatrogenic histopathologic changes are lacking. The clinical significance and long-term implications of multiple small foci of electrode-induced injury that remain in the patient's brain after resection of the epileptogenic focus are unknown and may provide a welcome area for future study.

Enhanced clinical task-based fMRI metrics through locally low-rank denoising of complex-valued data.

OBJECTIVE: This study investigates a locally low-rank (LLR) denoising algorithm applied to source images from a clinical task-based functional MRI (fMRI) exam before post-processing for improving statistical confidence of task-based activation maps. METHODS: Task-based motor and language fMRI was obtained in eleven healthy volunteers under an IRB approved protocol. LLR denoising was then applied to raw complex-valued image data before fMRI processing. Activation maps generated from conventional non-denoised (control) data were compared with maps derived from LLR-denoised image data. Four board-certified neuroradiologists completed consensus assessment of activation maps; region-specific and aggregate motor and language consensus thresholds were then compared with nonparametric statistical tests. Additional evaluation included retrospective truncation of exam data without and with LLR denoising; a ROI-based analysis tracked t-statistics and temporal SNR (tSNR) as scan durations decreased. A test-retest assessment was performed; retest data were matched with initial test data and compared for one subject. RESULTS: fMRI activation maps generated from LLR-denoised data predominantly exhibited statistically significant (p = 4.88×10-4 to p = 0.042; one p = 0.062) increases in consensus t-statistic thresholds for motor and language activation maps. Following data truncation, LLR data showed task-specific increases in t-statistics and tSNR respectively exceeding 20 and 50% compared to control. LLR denoising enabled truncation of exam durations while preserving cluster volumes at fixed thresholds. Test-retest showed variable activation with LLR data thresholded higher in matching initial test data. CONCLUSION: LLR denoising affords robust increases in t-statistics on fMRI activation maps compared to routine processing, and offers potential for reduced scan duration while preserving map quality.

Minimizing susceptibility-induced BOLD sensitivity loss in multi-band accelerated fMRI using point spread function mapping and gradient reversal.

Objective. Interleaved reverse-gradient fMRI (RG-fMRI) with a point-spread-function (PSF) mapping-based distortion correction scheme has the potential to minimize signal loss in echo-planar-imaging (EPI). In this work, the RG-fMRI is further improved by imaging protocol optimization and application of reverse Fourier acquisition.Approach. Multi-band imaging was adapted for RG-fMRI to improve the temporal and spatial resolution. To better understand signal dropouts in forward and reverse EPIs, a simple theoretical relationship between echo shift and geometric distortion was derived and validated by the reliable measurements using PSF mapping method. After examining practical imaging protocols for RG-fMRI in three subjects on both a conventional whole-body and a high-performance compact 3 T, the results were compared and the feasibility to further improve the RG-fMRI scheme were explored. High-resolution breath-holding RG-fMRI was conducted with nine subjects on the compact 3 T and the fMRI reliability improvement in high susceptibility brain regions was demonstrated. Finally, reverse Fourier acquisition was applied to RG-fMRI, and its benefit was assessed by a simulation study based on the breath-holding RG-fMRI data.Main results. The temporal and spatial resolution of the multi-band RG-fMRI became feasible for whole-brain fMRI. Echo shift measurements from PSF mapping well estimated signal dropout effects in the EPI pair and were useful to further improve the RG-fMRI scheme. Breath-holding RG-fMRI demonstrated improved fMRI reliability in high susceptibility brain regions. Reverse partial Fourier acquisition omitting the late echoes could further improve the temporal or spatial resolution for RG-fMRI without noticeable signal degradation and spatial resolution loss.Significance. With the improved imaging scheme, RG-fMRI could reliably investigate the functional mechanisms of the human brain in the temporal and frontal areas suffering from susceptibility-induced functional sensitivity loss.

Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors.

CRISPR interference (CRISPRi) enables programmable, reversible, and titratable repression of gene expression (knockdown) in mammalian cells. Initial CRISPRi-mediated genetic screens have showcased the potential to address basic questions in cell biology, genetics, and biotechnology, but wider deployment of CRISPRi screening has been constrained by the large size of single guide RNA (sgRNA) libraries and challenges in generating cell models with consistent CRISPRi-mediated knockdown. Here, we present next-generation CRISPRi sgRNA libraries and effector expression constructs that enable strong and consistent knockdown across mammalian cell models. First, we combine empirical sgRNA selection with a dual-sgRNA library design to generate an ultra-compact (1-3 elements per gene), highly active CRISPRi sgRNA library. Next, we compare CRISPRi effectors to show that the recently published Zim3-dCas9 provides an excellent balance between strong on-target knockdown and minimal non-specific effects on cell growth or the transcriptome. Finally, we engineer a suite of cell lines with stable expression of Zim3-dCas9 and robust on-target knockdown. Our results and publicly available reagents establish best practices for CRISPRi genetic screening.

Microbiota and adipocyte mitochondrial damage in type 2 diabetes are linked by Mmp12+ macrophages.

Microbiota contribute to the induction of type 2 diabetes by high-fat/high-sugar (HFHS) diet, but which organs/pathways are impacted by microbiota remain unknown. Using multiorgan network and transkingdom analyses, we found that microbiota-dependent impairment of OXPHOS/mitochondria in white adipose tissue (WAT) plays a primary role in regulating systemic glucose metabolism. The follow-up analysis established that Mmp12+ macrophages link microbiota-dependent inflammation and OXPHOS damage in WAT. Moreover, the molecular signature of Mmp12+ macrophages in WAT was associated with insulin resistance in obese patients. Next, we tested the functional effects of MMP12 and found that Mmp12 genetic deficiency or MMP12 inhibition improved glucose metabolism in conventional, but not in germ-free mice. MMP12 treatment induced insulin resistance in adipocytes. TLR2-ligands present in Oscillibacter valericigenes bacteria, which are expanded by HFHS, induce Mmp12 in WAT macrophages in a MYD88-ATF3-dependent manner. Thus, HFHS induces Mmp12+ macrophages and MMP12, representing a microbiota-dependent bridge between inflammation and mitochondrial damage in WAT and causing insulin resistance.

Neural activity in trigeminal neuralgia patients with sensory and motor stimulations: A pilot functional MRI study.

OBJECTIVE: Trigeminal neuralgia (TN) is a neuropathic pain syndrome that typically exhibits paroxysmal pain. However, the true mechanism of pain processing is unclear. We aim to evaluate the neural activity changes, before and after radiofrequency rhizotomy, in TN patients using functional MRI (fMRI) with sensory and motor stimulations. METHODS: Six patients with classical TN participated in the study. Each patient underwent two boxcar paradigms of fMRI tasks: air-sensation and jaw-clenching around 1-3 weeks before and after the surgical intervention. McGill Pain Questionnaire (MPQ) was used to evaluate the pain intensity prior to fMRI study. RESULTS: Before rhizotomy, the jaw-clenching stimulation yielded reduced brain activation in primary motor (M1) and primary (SI) and secondary somatosensory (SII) cortices. Following intervention, activation in those regions returned to near normal levels observed in healthy subjects. For air-sensation stimulation, several pain and pain modulation regions such as right thalamus, right putamen, insula, and brainstem, were activated before the intervention, but subsided after the intervention. This correlated well with the change of MPQ scores (p < 0.01). CONCLUSIONS: In our study, we observed significant pain reduction accompanied by increased motor activities after rhizotomy in patients with TN. We hypothesize that the reduced motor activities identified in fMRI may be reversed after the treatment with radiofrequency rhizotomy. More research is warranted.

Intestinal microbiota signatures of clinical response and immune-related adverse events in melanoma patients treated with anti-PD-1.

Ample evidence indicates that the gut microbiome is a tumor-extrinsic factor associated with antitumor response to anti-programmed cell death protein-1 (PD-1) therapy, but inconsistencies exist between published microbial signatures associated with clinical outcomes. To resolve this, we evaluated a new melanoma cohort, along with four published datasets. Time-to-event analysis showed that baseline microbiota composition was optimally associated with clinical outcome at approximately 1 year after initiation of treatment. Meta-analysis and other bioinformatic analyses of the combined data show that bacteria associated with favorable response are confined within the Actinobacteria phylum and the Lachnospiraceae/Ruminococcaceae families of Firmicutes. Conversely, Gram-negative bacteria were associated with an inflammatory host intestinal gene signature, increased blood neutrophil-to-lymphocyte ratio, and unfavorable outcome. Two microbial signatures, enriched for Lachnospiraceae spp. and Streptococcaceae spp., were associated with favorable and unfavorable clinical response, respectively, and with distinct immune-related adverse effects. Despite between-cohort heterogeneity, optimized all-minus-one supervised learning algorithms trained on batch-corrected microbiome data consistently predicted outcomes to programmed cell death protein-1 therapy in all cohorts. Gut microbial communities (microbiotypes) with nonuniform geographical distribution were associated with favorable and unfavorable outcomes, contributing to discrepancies between cohorts. Our findings shed new light on the complex interaction between the gut microbiome and response to cancer immunotherapy, providing a roadmap for future studies.

Separase cleaves the kinetochore protein Meikin at the meiosis I/II transition.

To generate haploid gametes, germ cells undergo two consecutive meiotic divisions requiring key changes to the cell division machinery. Here, we demonstrate that the protease separase rewires key cell division processes at the meiosis I/II transition by cleaving the meiosis-specific protein Meikin. Separase proteolysis does not inactivate Meikin but instead alters its function to create a distinct activity state. Full-length Meikin and the C-terminal Meikin separase cleavage product both localize to kinetochores, bind to Plk1 kinase, and promote Rec8 cleavage, but our results reveal distinct roles for these proteins in controlling meiosis. Mutations that prevent Meikin cleavage or that conditionally inactivate Meikin at anaphase I result in defective meiosis II chromosome alignment in mouse oocytes. Finally, as oocytes exit meiosis, C-Meikin is eliminated by APC/C-mediated degradation prior to the first mitotic division. Thus, multiple regulatory events irreversibly modulate Meikin activity during successive meiotic divisions to rewire the cell division machinery at two distinct transitions.