bluuebunny/crossref_metadata_2025 huggingface dataset:
Advancing the communication of genetic risk for cardiometabolic diseases: A critical interpretive synthesis
Authors: Law Jing Hui , Sultan Najia , Finer Sarah , Fudge Nina
Published: May 2023

Background

Genetics play an important role in risk for cardiometabolic diseases—including type 2 diabetes, cardiovascular disease and obesity. Existing research has explored the clinical utility of genetic risk tools such as polygenic risk scores—and whether interventions communicating genetic risk information using these tools can impact on individuals’ cognitive appraisals of disease risk and/or preventative health behaviours. Previous systematic reviews exploring the evidence base suggest mixed results. To expand current understanding and address knowledge gaps, we undertook a reflexive method of evidence synthesis to the literature—questioning the theoretical basis behind current interventions that communicate genetic risk information and exploring how the effects of genetic risk tools can be fully harnessed for cardiometabolic diseases.

Methods

We obtained 188 records from a combination of database, website and grey literature searches—supplemented with reference chaining and expert subject knowledge within the review team. Using pre-defined critical interpretive synthesis methods, quantitative and qualitative evidence was synthesised and critiqued alongside theoretical understanding from surrounding fields of behavioural and social sciences.

Findings

Existing interventions communicating genetic risk information focus predominantly on the “self”, targeting individual-level cognitive appraisals, such as perceived risk and perceived behavioural control. This approach risks neglecting the role of contextual factors and upstream determinants that can reinforce individuals’ interpretations of risk. It also assumes target populations to embody an “ascetic subject of compliance”—the idea of a patient who strives to comply diligently with professional medical advice, logically and rationally adopting any recommended lifestyle changes. We developed a synthesising argument—beyond the “ascetic subject of compliance”—grounded in three major limitations of this perspective: (1) Difficulty applying existing theories/models to diverse populations; (2) The role of familial variables and (3) The need for a life course perspective.

Conclusions

Interventions communicating genetic risk information should account for wider influences that can affect individuals’ responses to risk at different levels—including through interactions with their family systems, socio-cultural environments and wider health provision.

Protocol registration

PROSPERO CRD42021289269
Deep learning for rapid and reproducible histology scoring of lung injury in a porcine model
Authors: Silva Iran A. N. , Rashed Salma Kazemi , Hedlund Ludwig , Lidfeldt August , Gvazava Nika , Stegmayr John , Skoryk Valeriia , Aits Sonja , Wagner Darcy E
Published: May 2023

Acute respiratory distress syndrome (ARDS) is a life-threatening condition with mortality rates between 30-50%. Althoughin vitromodels replicate some aspects of ARDS, small and large animal models remain the primary research tools due to the multifactorial nature of the disease. When using these animal models, histology serves as the gold standard method to confirm lung injury and exclude other diagnoses as high-resolution chest images are often not feasible. Semi-quantitative scoring performed by independent observers is the most common form of histologic analysis in pre-clinical animal models of ARDS. Despite progress in standardizing analysis procedures, objectively comparing histological injuries remains challenging, even for highly-trained pathologists. Standardized scoring simplifies the task and allows better comparisons between research groups and across different injury models, but it is time-consuming, and interobserver variability remains a significant concern. Convolutional neural networks (CNNs), which have emerged as a key tool in image analysis, could automate this process, potentially enabling faster and more reproducible analysis. Here we explored the reproducibility of human standardized scoring for an animal model of ARDS and its suitability for training CNNs for automated scoring at the whole slide level. We found large variations between human scorers, even for pre-clinical experts and board-certified pathologies in evaluating ARDS animal models. We demonstrate that CNNs (VGG16, EfficientNetB4) are suitable for automated scoring and achieve up to 83% F1-score and 78% accuracy. Thus, CNNs for histopathological classification of acute lung injury could help reduce human variability and eliminate a time-consuming manual research task with acceptable performance.
Coordinated Chemokine Expression Defines Macrophage Subsets Across Tissues
Authors: Li Xin , Mara Arlind B. , Musial Shawn , Rawat Kavita , King William T. , Kolling Fred W. , Gerebtsov Nikita , Jakubzick Claudia V.
Published: May 2023

Tissue-resident macrophages in the lung comprising alveolar and interstitial macrophages (IMs) display a high degree of heterogeneity. In general, macrophage heterogeneity is thought to arise from various forms of activation that are heavily confounded by the recruitment of monocytes to the tissue-resident macrophage pool. To better understand the functional heterogeneity of IMs in the lung, we profiled the transcription of resident CD206hiand CD206loIMs under steady-state and inflammatory conditions, excluding recruited macrophages. Rather than observing conventionalin vitroM1 and M2 activation states, we identified seven chemokine-expressing IM subsets: IMck1 (Ccl2, Ccl7, Ccl12,and someCxcl14), IMck2-4 (Ccl3, Ccl4, Ccl5, Cxcl1, Cxcl2,andCxcl3), IMck5 (Ccl8), IMck6 (Ccl6andCcl9), IMck7 (Cxcl9andCxcl10), IMck8 (Cxcl13), and IMck9 (Ccl24), which were found in steady-state or induced by acute inflammation. Beyond the mouse lung, similar coordinated chemokine signatures were observed in macrophages and monocytes from other tissues and across species. Although all IMs expressedPf4(CXCL4), mainly CD206hiIMs were selectively depleted inPf4CreR26EYFP-DTRmice. Loss of CD206hiIMs resulted in significantly reduced inflammatory cell influx in allergen- and infection-driven models, as well as significantly diminished tertiary lymphoid formation and subsequent accumulation of GL7+germinal center B cells. Overall, our study highlights a division of labor among interstitial macrophages, reflected by the coordinated production of chemokines to control inflammatory cell influx and organize tertiary lymphoid tissue architecture.

One Sentence Summary

The study highlights a division of labor among interstitial macrophages, reflected by the coordinated production of chemokines to control inflammatory cell influx and organize tertiary lymphoid tissue architecture.
Whole Transcriptome and Functional Analyses Identify Novel Genes Involved in Meiosis and Fertility inDrosophila melanogaster
Authors: Sun Siqi , Defosse Tyler , Boyd Ayla , Sop Joel , Verderose Faith , Surray Diya , Aziz Mark , Howland Margaret , Wu Siwen , Changela Neha , Jang Janet , Schindler Karen , Xing Jinchuan , McKim Kim S.
Published: May 2023

Reproductive success requires the development of viable oocytes and the accurate segregation of chromosomes during meiosis. Failure to segregate chromosomes properly can lead to infertility, miscarriages, or developmental disorders. A variety of factors contribute to accurate chromosome segregation and oocyte development, such as spindle assembly and sister chromatid cohesion. However, many proteins required for meiosis remain unknown. In this study, we aimed to identify and characterize novel meiotic and fertility genes using the genome ofDrosophila melanogaster. To accomplish this goal, genes upregulated within meiotically active tissues were identified. About 200 genes with no known function were silenced using RNA interference (RNAi), and the effects on meiosis and fertility were assessed. We identified 65 genes that when silenced caused infertility and/or high levels of chromosomal nondisjunction. The vast majority of these genes have human and mouse homologs that are also poorly studied. Through this screening process, we identified novel genes that are crucial for meiosis and oocyte development but have not been extensively studied in human or model organisms. Understanding the function of these genes will be an important step towards the understanding of their biological significance during reproduction.

Author Summary

In this study, we aimed to identify and characterize novel meiotic and fertility genes within the genome ofDrosophila melanogaster. We identified 65 genes that when silenced caused infertility and/or high levels of chromosomal nondisjunction. The vast majority of these genes have human and mouse homologs that are also poorly studied. Through this screening process, we identified novel genes that are crucial for meiosis and oocyte development, making them strong candidates for future studies to characterize their functions.
LRP10 as a novel α-synuclein regulator in Lewy body diseases
Authors: Mascaro Ana Carreras , Grochowska Martyna M. , Boumeester Valerie , Dits Natasja F. J. , Bilgiҫ Ece Naz , Breedveld Guido J. , Vergouw Leonie , de Jong Frank Jan , van Royen Martin E. , Bonifati Vincenzo , Mandemakers Wim
Published: May 2023

Autosomal dominant variants inLRP10have been identified in patients with Lewy body diseases (LBDs), including Parkinson’s disease (PD), Parkinson’s disease-dementia (PDD), and dementia with Lewy bodies (DLB). Nevertheless, there is little mechanistic insight into the role of LRP10 in disease pathogenesis. In the brains of non-demented individuals, LRP10 is typically expressed in non-neuronal cells like astrocytes and neurovasculature, but in idiopathic and genetic cases of PD, PDD, and DLB it is also present in α-synuclein-positive neuronal Lewy bodies. These observations raise the questions of what leads to the accumulation of LRP10 in Lewy bodies and whether a possible interaction between LRP10 and α-synuclein plays a role in disease pathogenesis. Here, we demonstrate that wild-type LRP10 is secreted via extracellular vesicles (EVs) and can be internalised via clathrin-dependent endocytosis. Additionally, we show that LRP10 secretion is highly sensitive to autophagy inhibition, which induces the formation of atypical LRP10 vesicular structures in neurons in human induced pluripotent stem cells (iPSC)-derived midbrain-like organoids (hMLOs). Furthermore, we show that LRP10 overexpression leads to a strong induction of monomeric α-synuclein secretion, together with time-dependent, stress-sensitive changes in intracellular α-synuclein levels. Interestingly, patient-derived astrocytes carrying thec.1424+5G>A LRP10variant secrete aberrant high-molecular-weight species of LRP10 in EV-free media fractions. Finally, we show that the truncated LRP10spliceprotein binds to wild-type LRP10, reduces LRP10 wild-type levels, and antagonises the regulatory effect of LRP10 on α-synuclein levels and distribution. Together, this work provides initial evidence for a functional role of LRP10 in LBDs by regulating intra- and extracellular α-synuclein levels, and pathogenic mechanisms linked to the disease-associatedc.1424+5G>A LRP10variant, pointing towards potentially important disease mechanisms in LBDs.
Anti-nuclear antibody (ANA) detection in culture supernatant of cloned B cells
Authors: Haque Shabirul , Watanabe Manami , Atisha-Fregoso Yemil , Diamond Betty
Published: May 2023

Anti-nuclear antibodies (ANA) of individuals with SLE contribute to disease pathogenesis and tissue injury. Systematic analysis of the fine specificity of ANA produced by individual B cells has been limited, in part, to the low concentration of immunoglobulin in single B cell cultures. We modified single B cell culture methods and developed an ANA ELISA to detect ANA at very low levels (15.0 ng/ml) of IgM in the supernatant of clonally expanded B cell cultures. This approach allows for the analysis of ANA reactivity of the IgM produced by approximately 60% of the single sorted naive B cells expanded in culture and permits a relatively high throughput evaluation at the single cell level of the ANA reactivity of naïve B cells of healthy individuals and patients with autoimmune diseases.
Functional Characterization of Calmodulin-like Proteins, CML13 and CML14, as Novel Light Chains of Arabidopsis Class VIII Myosins
Authors: Symonds Kyle , Teresinski Howard J. , Hau Bryan , Sadot Einat , Dwivedi Vikas , Belausov Eduard , Bar-Sinai Sefi , Tominaga Motoki , Haraguchi Takeshi , Ito Kohji , Snedden Wayne A.
Published: May 2023

Myosins are important motor proteins that associate with the actin cytoskeleton. Structurally, myosins function as heteromeric complexes where smaller light chains, such as calmodulin (CaM), bind to isoleucine-glutamine (IQ) domains in the neck regions to facilitate mechano-enzymatic activity. We recently identified Arabidopsis CaM-like (CML) proteins, CML13 and CML14 as interactors of proteins containing multiple IQ domains, including a member of the myosin VIII class. Here, usingin vivoandin vitroassays we demonstrate that CaM, CML13, and CML14 bind the neck region of all four Arabidopsis myosin VIII isoforms. Among ten CML isoforms tested forin plantabinding to myosins VIIIs, CaM, CML13, and CML14 gave the strongest signals usingin plantasplit-luciferase protein-interaction assays.In vitro,recombinant CaM, CML13, and CML14 showed specific, high-affinity, calcium-independent binding to the IQ domains of myosin VIIIs. Subcellular localization analysis indicated that CaM, CML13, and CML14 co-localized to plasma membrane-bound puncta when co-expressed with RFP-myosin fusion proteins containing IQ- and tail-domains of myosin VIIIs. In addition,in vitroactin-motility assays using recombinant myosin holoenzymes demonstrated that CaM, CML13, and CML14 function as light chains for myosin VIIIs. Collectively, our data indicate that Arabidopsis CML13 and CML14 are novel myosin VIII light chains.

Highlight

Myosins are key proteins in the plant cytoskeleton, but the identity of their light chain components is unknown. Here, we show that calmodulin-like proteins function as novel myosin light chains.
Non-micellar ganglioside GM1 induces an instantaneous conformational change in Aβ42leading to the modulation of the peptide amyloid-fibril pathway
Authors: Kumar Manjeet , Ivanova Magdalena I , Ramamoorthy Ayyalusamy
Published: May 2023

Alzheimer’s disease is a progressive degenerative condition that mainly affects cognition and memory. Recently, distinct clinical and neuropathological phenotypes have been identified in AD. Studies revealed that structural variation in Aβ fibrillar aggregates correlates with distinct disease phenotypes. Moreover, environmental surroundings, including other biomolecules such as proteins and lipids, have been shown to interact and modulate Aβ aggregation. Model membranes containing ganglioside (GM1) clusters are specifically known to promote Aβ fibrillogenesis. This study unravels the modulatory effect of non-micellar GM1, a glycosphingolipid frequently released from the damaged neuronal membranes, on Aβ42amyloid fibril formation. Using far-UV circular dichroism experiments, we observed a spontaneous change in the peptide secondary structure from random-coil to β-turn with subsequent generation of predominantly β-sheet-rich species upon interaction with GM1. Thioflavin-T (ThT) fluorescence assays further indicated that GM1 interacts with the amyloidogenic Aβ42primary nucleus leading to a possible formation of GM1-modified Aβ42fibril. Statistically, no significant difference in toxicity to RA-differentiated SH-SY5Y cells was observed between Aβ42fibrils and GM1-tweaked Aβ42aggregates. Moreover, GM1-modified Aβ42aggregates exhibited prion-like properties in catalyzing the amyloid fibril formation of both major isomers of Aβ, Aβ40, and Aβ42.
Serotonin modulates infraslow oscillation in the dentate gyrus during Non-REM sleep
Authors: Turi Gergely F. , Teng Sasa , Chen Xinyue , Lim Emily CY , Dias Carla , Hu Ruining , Wang Ruizhi , Zhen Fenghua , Peng Yueqing
Published: May 2023

Synchronous neuronal activity is organized into neuronal oscillations with various frequency and time domains across different brain areas and brain states. For example, hippocampal theta, gamma and sharp wave oscillations are critical for memory formation and communication between hippocampal subareas and the cortex. In this study, we investigated the neuronal activity of the dentate gyrus (DG) with optical imaging tools during sleep-wake cycles. We found that the activity of major glutamatergic cell populations in the DG is organized into infraslow oscillations (0.01 – 0.03 Hz) during NREM sleep. Although the DG is considered a sparsely active network during wakefulness, we found that 50% of granule cells and about 25% of mossy cells exhibit increased activity during NREM sleep, compared to that during wakefulness. Further experiments revealed that the infraslow oscillation in the DG was correlated with rhythmic serotonin release during sleep, which oscillates at the same frequency but in an opposite phase. Genetic manipulation of 5-HT receptors revealed that this neuromodulatory regulation is mediated by 5-HT1a receptors and the knockdown of these receptors leads to memory impairment. Together, our results provide novel mechanistic insights into how the 5-HT system can influence hippocampal activity patterns during sleep.
Decreasing the flexibility of the TELSAM-target protein linker and omitting the cleavable fusion tag improves crystal order and diffraction limits
Authors: Gajjar Parag L. , Romo Maria J. Pedroza , Litchfield Celeste M. , Callahan Miles , Redd Nathan , Nawarathnage Supeshala , Soleimani Sara , Averett Jacob , Wilson Elijah , Lewis Andrew , Stewart Cameron , Tseng Yi-Jie J. , Doukov Tzanko , Lebedev Andrey , Moody James D.
Published: May 2023

TELSAM crystallization promises to become a revolutionary tool for the facile crystallization of proteins. TELSAM can increase the rate of crystallization and form crystals at low protein concentrations without direct contact between TELSAM polymers and, in some cases, with very minimal crystal contacts overall (Nawarathnageet al., 2022). To further understand and characterize TELSAM-mediated crystallization, we sought to understand the requirements for the composition of the linker between TELSAM and the fused target protein. We evaluated four different linkers Ala-Ala, Ala-Val, Thr-Val, and Thr-Thr, between 1TEL and the human CMG2 vWa domain. We compared the number of successful crystallization conditions, the number of crystals, the average and best diffraction resolution, and the refinement parameters for the above constructs. We also tested the effect of the fusion protein SUMO on crystallization. We discovered that rigidification of the linker improved diffraction resolution, likely by decreasing the number of possible orientations of the vWa domains in the crystal, and that omitting the SUMO domain from the construct also improved the diffraction resolution.

Synopsis

We demonstrate that the TELSAM protein crystallization chaperone can enable facile protein crystallization and high-resolution structure determination. We provide evidence to support the use of short but flexible linkers between TELSAM and the protein of interest and to support the avoidance of cleavable purification tags in TELSAM-fusion constructs.
Drug Repurposing using consilience of Knowledge Graph Completion methods
Authors: Tu Roger , Sinha Meghamala , González Carolina , Hu Eric , Dhuliawala Shehzaad , McCallum Andrew , Su Andrew I.
Published: May 2023

While link prediction methods in knowledge graphs have been increasingly utilized to locate potential associations between compounds and diseases, they suffer from lack of sufficient evidence to explain why a drug and a disease may be indicated. This is especially true for knowledge graph embedding (KGE) based methods where a drug-disease indication is linked only by information gleaned from a vector representation. Complementary pathwalking algorithms can increase the confidence of drug repurposing candidates by traversing a knowledge graph. However, these methods heavily weigh the relatedness of drugs, through their targets, pharmacology or shared diseases. Furthermore, these methods can rely on arbitrarily extracted paths as evidence of a compound to disease indication and lack the ability to make predictions on rare diseases. In this paper, we evaluate seven link prediction methods on a vast biomedical knowledge graph for drug repurposing. We follow the principle of consilience, and combine the reasoning paths and predictions provided by path-based reasoning approaches with those of KGE methods to identify putative drug repurposing indications. Finally, we highlight the utility of our approach through a potential repurposing indication.
Genomic epidemiology ofTreponema pallidumand circulation of strains with diminishedtprKantigen variation capability in Seattle, 2021-2022
Authors: Lieberman Nicole A.P. , Avendaño Carlos , Mohamed Bakhash Shah A. K. , Nunley Ethan , Xie Hong , Giacani Lorenzo , Berzkalns Anna , Soge Olusegun O. , Reid Tara B. , Golden Matthew R. , Greninger Alexander L.
Published: May 2023

Background

Syphilis incidence continues to increase dramatically in the United States and yet little is known aboutTreponema pallidum(TP) genomic epidemiology within American metropolitan areas.

Methods

We performed whole genome sequencing andtprKdeep sequencing of 28 TP-containing specimens collected mostly from remnant Aptima swabs from 24 individuals from Seattle Sexual Health Clinic during 2021-2022.

Results

All 12 individuals infected with Nichols lineage strains were MSM, while a specific SS14 cluster (average 0.33 SNPs) included 1 MSW and five women. All TP strains sequenced were azithromycin resistant via 23S rRNA A2058G mutation. Identical TP genomic sequences were found in pharyngeal and rectal swab specimens taken from the same individuals concurrently.tprKsequences were less variable between patient-matched specimens and between epidemiologically-linked clusters. We detected a 528 bp deletion in thetprKdonor site locus, eliminating ninetprKdonor sites, in TP genomes of three individuals with secondary syphilis, associated with diminution of overalltprKsequence diversity.

Conclusions

We developed an end-to-end workflow for public health genomic surveillance of TP from remnant Aptima swab specimens. With its high rate of gene conversion,tprKsequencing may assist in linking cases beyond routine TP genome sequencing. TP strains with deletions intprKdonor sites currently circulate and are associated with diminished antigenic diversity of the TprK putative outer membrane protein.
A programmable and site-specific anchoring system for biophysical analysis of DNA:protein interactions on large topologically closed DNA molecules
Authors: Gilhooly Neville S. , Kowalczykowski Stephen C.
Published: May 2023

Single-molecule and bulk biophysical approaches to study protein-DNA interactions on surface-immobilised nucleic acid templates typically rely on modifying the ends of linear DNA molecules to enable surface-DNA attachments. Unless both strands are constrained, this results in topologically-free DNA molecules and the inability to observe supercoiling-dependent biological processes, or requires additional means to micro-manipulate the free DNA end to impose rotational constraints or induce supercoiling. We developed a method using RecA protein to induce the formation of a circularised compliment-stabilised D-loop. The resulting joint molecule is topologically closed, surface anchorable and stable under microfluidic flow. Importantly, the method obviates the need for subsequent manipulation of surface tethered DNA; tethered molecules remain supercoiled and retain accessibility to DNA binding proteins. This approach adds to the toolkit for those studying processes on DNA that require supercoiled DNA templates or topologically constrained systems.

WHY IT MATTERS

Supercoiling plays an important role in regulating genetic processes such as DNA replication and transcription. We have developed a facile method to immobilise large (supra diffraction-limited) supercoiled DNA substrates without the need for complex trapping modalities to allow biophysical interrogation of the surface-tethered DNA molecules. This will expand the toolkit for experimentalists interested in studying protein-DNA interactions at the single-molecule or ensemble level requiring the use of topologically closed or supercoiling-dependent systems such as origin-dependent bacterial DNA replication.
Dysregulated TDP-43 proteostasis perturbs excitability of spinal motor neurons during brainstem-mediated fictive locomotion in zebrafish
Authors: Asakawa Kazuhide , Handa Hiroshi , Kawakami Koichi
Published: May 2023

Spinal motor neurons (SMNs) are the primary target of degeneration in amyotrophic lateral sclerosis (ALS). Degenerating motor neurons accumulate cytoplasmic TAR DNA-binding protein 43 (TDP-43) aggregates in most ALS cases. This SMN pathology can occur without mutation in the coding sequence of the TDP-43-encoding gene, TARDBP. Whether and how wild-type TDP-43 drives pathological changes in SMNs in vivo remain largely unexplored. In this study, we develop a two-photon calcium imaging setup in which tactile-evoked neural responses of motor neurons in the brainstem and spinal cord can be monitored using the calcium indicator GCaMP. We devise a piezo-assisted tactile stimulator that reproducibly evokes a brainstem descending neuron upon tactile stimulation of the head. A direct comparison between caudal primary motor neurons (CaPs) with or without TDP-43 overexpression in contiguous spinal segments demonstrates that CaPs overexpressing TDP-43 display attenuated Ca2+transients during fictive escape locomotion evoked by the tactile stimulation. These results show that excessive amounts of TDP-43 protein reduce the neuronal excitability of SMNs and potentially contribute to asymptomatic pathological lesions of SMNs and movement disorders in patients with ALS.
Diabetes and Incidence of Breast Cancer and its Molecular Subtypes: A Systematic Review and Meta-Analysis
Authors: Xiong Fanxiu , Dai Qichen , Zhang Sihan , Bent Stephen , Tahir Peggy , Van Blarigan Erin L. , Kenfield Stacey A. , Chan June M. , Schmajuk Gabriela , Graff Rebecca E.
Published: May 2023

Diabetes mellitus (DM) has been proposed to be positively associated with breast cancer (BCa) risk due to shared risk factors, metabolic dysfunction, and use of antidiabetic medications. We conducted a systematic review and meta-analysis to evaluate the association between DM and BCa risk. We searched PubMed, Embase, and Web of Science for cohort and case-control studies assessing the association between DM and BCa published before December 10, 2021. Two reviewers independently screened the studies for inclusion, abstracted article data, and rated study quality. Random effects models were used to estimate summary risk ratios (RRs) and 95% confidence intervals (CIs). From 8396 articles identified in the initial search, 70 independent studies were included in the meta-analysis. DM was associated with an overall increased risk of BCa (RR=1.20, 95% CI: 1.11-1.29). The 24 case-control studies demonstrated a stronger association (RR=1.26, 95% CI: 1.13-1.40) than the 46 cohort studies (RR=1.15, 95% CI: 1.05-1.27). Studies reporting risk by menopausal status found that postmenopausal women had an elevated risk of developing BCa (RR=1.12, 95% CI: 1.07-1.17). No association between DM and BCa risk was observed among premenopausal women (RR=0.95, 95% CI: 0.85-1.05). In addition, DM was associated with significantly increased risks of estrogen receptor (ER)+ (RR=1.09, 95% CI: 1.00-1.20), ER- (RR=1.16, 95% CI: 1.04-1.30), and triple negative BCa (RR=1.41, 95% CI: 1.01-1.96). The association estimate for human epidermal growth factor 2- positive BCa was also positive (RR=1.21, 95% CI: 0.52-2.82), but the confidence interval was wide and crossed the null. Our meta-analysis confirms a modest positive association between DM and BCa risk. In addition, our results suggest that the DM and BCa association may be modified by menopausal status, and DM may be differentially associated with BCa subtypes defined by receptor status. Additional studies are warranted to investigate the mechanisms underlying these associations and any influence of DM on BCa receptor expression.
A framework for ultra-low input spatial tissue proteomics
Authors: Makhmut Anuar , Qin Di , Fritzsche Sonja , Nimo Jose , König Janett , Coscia Fabian
Published: May 2023

Spatial tissue proteomics combining microscopy-based cell phenotyping with ultra-sensitive mass spectrometry (MS)-based proteomics is an emerging and powerful concept for the study of cell function and heterogeneity in health and disease. However, optimized workflows that preserve morphological information for image-based phenotype discovery and maximize proteome coverage of few or even single cells from laser microdissected archival tissue, are currently lacking. Here, we report a robust and scalable workflow for the proteomic analysis of ultra-low input formalin-fixed, paraffin-embedded (FFPE) material. Benchmarking in the murine liver resulted in up to 2,000 quantified proteins from single hepatocyte contours and nearly 5,000 proteins from 50-cell regions with high quantitative reproducibility. Applied to human tonsil, we profiled 146 microregions including spatially defined T and B lymphocyte niches and quantified cell type specific markers, cytokines, immune cell regulators and transcription factors. These rich data also highlighted proteome dynamics in spatially defined zones of activated germinal centers, illuminating sites undergoing active B-cell proliferation and somatic hypermutation. Our results demonstrate the power of spatially-resolved proteomics for tissue phenotyping by integrating high-content imaging, laser microdissection, and ultra-sensitive mass spectrometry. This approach has broad implications for a wide range of biomedical applications, including early disease profiling, drug target discovery and biomarker research.
Zymoseptoria triticisuppresses the host immune response and facilitates the success of avirulent strains in mixed infections
Authors: Bernasconi Alessio , Lorrain Cécile , Flury Priska , Alassimone Julien , McDonald Bruce A. , Sánchez-Vallet Andrea
Published: May 2023

Plants interact with a plethora of pathogenic microorganisms in nature. Pathogen-plant interaction experiments focus mainly on single-strain infections, typically ignoring the complexity of multi-strain infections even though mixed infections are common and critical for the infection outcome. The wheat pathogenZymoseptoria triticiforms highly diverse fungal populations in which several pathogen strains often colonize the same leaf. Despite the importance of mixed infections, the mechanisms governing interactions between a mixture of pathogen strains within a plant host remain largely unexplored. Here we demonstrate that avirulent pathogen strains benefit from being in mixed infections with virulent strains. We show that virulent strains suppress the wheat immune response, allowing the avirulent strain to colonize the apoplast and to reproduce. Our experiments indicate that virulent strains in mixed infections can challenge the plant immune system both locally and systemically, providing a mechanistic explanation for the persistence of avirulent pathogen strains in fields planted to resistant host plants.
MSCProfiler: An image processing workflow to investigate Mesenchymal Stem Cell heterogeneity using imaging flow cytometry data
Authors: Gupta A. , Shaik S.K. , Balasubramanian L. , Chakraborty U
Published: May 2023

Single-cell immuno-heterogeneity has always been the forerunner of any change in homeostasis of cellular functions in the body. Mesenchymal stem cells represent a viable source for the development of cell-based therapies. Multiple conditions giving rise to inter, and intra-population variations result in heterogeneity and multipotent differentiation ability of these cells of stromal origin. Cell surface markers which are important members of membrane proteins, ion channels, transporter, adhesion, and signaling molecules generally differentiate between stromal cells of different origin. However, existing analytical tools cannot always model a pattern of their surface distribution in successive generations of growth and proliferation. In this study, we have developed a post-acquisition image analysis pipeline for human mesenchymal stromal cells obtained from exfoliated deciduous teeth (hSHEDs). Using the open-source image processing software CellProfiler, a pipeline has been developed to extract cellular features from 50,000-100,000 single-cell images. We made use of the image flow cytometry technology to explore the morphometric properties of hSHEDs, along with their surface marker distribution. This unbiased pipeline can extract cellular, geometrical and texture features such as shape, size, eccentricity, entropy, intensities as a measure of cellular heterogeneity. For the first time, we have described an automated, unbiased image assessment protocol implemented in a validated open-source software, leveraging the suite of image-based measurements to develop the prototype named as MSCProfiler. The hallmark of this screening workflow has been the identification and removal of image-based aberrations to identify the single-cell bright field and fluorescent images of mesenchymal stem cells.
Interindividual Diversity of Human Gut Mucin-Degrading Microbial Consortia
Authors: Fricker Ashwana D. , Yao Tianming , Lindemann Stephen R. , Flores Gilberto E.
Published: May 2023

Mucin is a glycoprotein secreted throughout the mammalian gastrointestinal tract that can support endogenous microorganisms in the absence of complex polysaccharides. While diverse mucin degrading bacteria have been identified, the individual host microbial community differences capable of metabolizing this complex polymer are not well described. To determine whether individuals have taxonomically distinct but functionally similar mucin-degrading communities, we used a ten-dayin vitrosequential batch culture fermentation from three human donors with mucin as the sole carbon source. For each donor, 16S rRNA gene amplicon sequencing was used to characterize microbial community succession, and the short-chain fatty acid profile was determined from the final community. Although two of the final communities had genus-level taxonomic differences signified by the presence ofDesulfovibrioandAkkermansia, other members, such asBacteroides, were shared between all three final communities. Metabolic output differences were most notable for one of the donor’s communities, with significantly less production of acetate and propionate than the other two communities. These findings reinforce the concept of a taxonomically distinct and, at broad levels, a functionally redundant gut microbiome. Furthermore, the mechanisms and efficiencies of mucin degradation across individuals are important for understanding how this community-level process impacts human health.
Visualization of the Cdc48 AAA+ ATPase protein unfolding pathway
Authors: Cooney Ian , Schubert Heidi L. , Cedeno Karina , Lin Hsien-Jung L. , Price John C , Hill Christopher P , Shen Peter S
Published: May 2023

The Cdc48 AAA+ ATPase is an abundant and essential enzyme that unfolds substrates in multiple protein quality control pathways. The enzyme includes two conserved AAA+ ATPase cassettes, D1 and D2, that assemble as hexameric rings with D1 stacked above D2. Here, we report an ensemble of structures of Cdc48 affinity purified from lysate in complex with the adaptor Shp1 in the act of unfolding substrate. Our analysis reveals a continuum of structural snapshots that spans the entire translocation cycle. These data reveal new elements of Shp1-Cdc48 binding and support a “hand-over-hand” mechanism in which the sequential movement of individual subunits is closely coordinated. D1 hydrolyzes ATP and disengages from substrate prior to D2, while D2 rebinds ATP and re-engages with substrate prior to D1, thereby explaining the dominant role played by D2 in substrate translocation/unfolding.
Living fast, dying young: anthropogenic habitat modification influences the fitness and life history traits of a cooperative breeder
Authors: Alaman Alejandro , Casas Enrique , Arbelo Manuel , Keynan Oded , Koren Lee
Published: May 2023

Modification of natural habitats can lead to an ecological trap, as animals can maladaptively select lower-quality habitats over natural landscapes. Modified habitats reduce group size and prevalence, the success of dispersing individuals, and breeding success. However, little is known about how these effects on fitness affect the sociality of cooperative breeding species, which may be particularly susceptible to habitat modification. Here we show that the selection of anthropogenically modified habitats negatively affects the fitness, which has consequences in the life history traits of a cooperative breeder.

We used data collected during six years from a monitored population of Arabian babblers (Argya squamiceps) and found that groups living in modified habitats breed more than those in natural habitats but that juvenile and adult survival in modified habitats was lower. Individuals living in modified habitats acquired dominance earlier than individuals from natural habitats. Males in modified habitats also dispersed earlier than those from natural habitats.

Our results suggest that modified habitats entail an ecological trap for Arabian babblers, which adjusts their life history traits as a response. Understanding the adaptation of social and cooperative breeding species to habitat modification is the first step for mitigating the processes behind human-related population declines.
PepPre: Promote Peptide Identification Using Accurate and Comprehensive Precursors
Authors: Tarn Ching , Wu Yu-Zhuo , Wang Kai-Fei
Published: May 2023

Accurate and comprehensive peptide precursor ions are crucial to tandem mass spectrometry-based peptide identification. An identification engine can greatly benefit from the search space reduction hinted by credible and detailed precursors. Additionally, both the number of identifications and the spectrum explainability can be increased by considering multiple precursors per spectrum. Here, we propose PepPre, which detects precursors by decomposing peaks into multiple isotope clusters using linear programming methods. The detected precursors are scored and ranked, and the high-scoring ones are used for the following peptide identification. PepPre is evaluated both on regular and cross-linked peptides datasets, and compared with 11 methods in this paper. The experimental results show that PepPre achieves 203% more PSM and 68% more peptide identifications than instrument software for regular peptides, and 99% more PSM and 27% more peptide pair identifications for cross-linked peptides, which also outperforms all other evaluated methods. In addition to the increased identification numbers, further credibility evaluation evidence that the identifications are credible. Moreover, by widening the isolation window of data acquisition from 2 Th to 8 Th, the engine is able to identify at least 64% more PSMs with PepPre, demonstrating the potential advantages of large isolation windows.

Graphical TOC Entry
Two distinct waves of transcriptome and translatome remodelling drive germline stem cell differentiation
Authors: Samuels Tamsin J. , Gui Jinghua , Gebert Daniel , Teixeira Felipe K.
Published: May 2023

Development and tissue maintenance require a supply of new cells, which are generated by division of stem cells and then specialised to perform their function. The differentiation process requires the tight control of gene expression, but this has been challenging to study in a systematic manner in adult stem cells, which are sparsely distributed in tissues. We have overcome these limitations by establishing a robust protocol to synchroniseDrosophilafemale germline stem cell (GSC) differentiationin vivo, allowing us to perform transcriptome and translatome analyses at high temporal resolution during differentiation. As well as observing dynamic changes in mRNA level, promoter usage and exon inclusion, our data reveal that changing translation efficiency is the predominant regulatory mechanism during GSC differentiation. Indeed, changes in mRNA level are frequently buffered by changes in translation efficiency, including the translational repression of transcripts that will only be translated later during oocyte maturation or embryo development. Contrary to the expected linear accumulation of changes from stem cell to differentiated cell, our data reveal that differentiation occurs through two distinct waves of changes in both the transcriptome and translatome level.
In Silico Investigations of Adaptive Therapy Using a Single Cytotoxic or a Single Cytostatic Drug
Authors: Saha Daniel K. , Anderson Alexander R. A. , Cisneros Luis , Maley Carlo C.
Published: May 2023

Adaptive therapy, as per the dose modulation, dose-skipping, or intermittent treatment protocol works well for treatment using a single cytotoxic drug, under a wide range of scenarios and parameter settings. In contrast, adaptive therapy works well only under a limited number of scenarios and parameter settings when using a single cytostatic drug. In general, adaptive therapy works best under conditions of higher fitness cost, higher replacement rate, higher turnover. Adaptive therapy works best when drug dosages are changed as soon as a change in tumor burden is detected. In general, it is better to pause treatment sooner than later, when the tumor is shrinking If the amount of drug used is too low, it is unable to control the sensitive cells and the tumor grows. However, if the drug dose is too high, it quickly selects for resistant cells and eventually the tumor grows out of control. However, there appears to be intermediate levels of dosing, which we call the minimum effective dose, which is able to control the sensitive cells but is not high enough to select for the resistant cells to grow out of control.
Heterogeneity-Preserving Discriminative Feature Selection for Subtype Discovery
Authors: M. A. Basher Abdur Rahman , Hallinan Caleb , Lee Kwonmoo
Published: May 2023

The discovery of subtypes is pivotal for disease diagnosis and targeted therapy, considering the diverse responses of different cells or patients to specific treatments. Exploring the heterogeneity within disease or cell states provides insights into disease progression mechanisms and cell differentiation. The advent of high-throughput technologies has enabled the generation and analysis of various molecular data types, such as single-cell RNA-seq, proteomic, and imaging datasets, at large scales. While presenting opportunities for subtype discovery, these datasets pose challenges in finding relevant signatures due to their high dimensionality. Feature selection, a crucial step in the analysis pipeline, involves choosing signatures that reduce the feature size for more efficient downstream computational analysis. Numerous existing methods focus on selecting signatures that differentiate known diseases or cell states, yet they often fall short in identifying features that preserve heterogeneity and reveal subtypes. To identify features that can capture the diversity within each class while also maintaining the discrimination of known disease states, we employed deep metric learning-based feature embedding to conduct a detailed exploration of the statistical properties of features essential in preserving heterogeneity. Our analysis revealed that features with a significant difference in interquartile range (IQR) between classes possess crucial subtype information. Guided by this insight, we developed a robust statistical method, termed PHet (Preserving Heterogeneity) that performs iterative subsampling differential analysis of IQR and Fisher’s method between classes, identifying a minimal set of heterogeneity-preserving discriminative features to optimize subtype clustering quality. Validation using public single-cell RNA-seq and microarray datasets showcased PHet’s effectiveness in preserving sample heterogeneity while maintaining discrimination of known disease/cell states, surpassing the performance of previous outlier-based methods. Furthermore, analysis of a single-cell RNA-seq dataset from mouse tracheal epithelial cells revealed, through PHet-based features, the presence of two distinct basal cell subtypes undergoing differentiation toward a luminal secretory phenotype. Notably, one of these subtypes exhibited high expression of BPIFA1. Interestingly, previous studies have linked BPIFA1 secretion to the emergence of secretory cells during mucociliary differentiation of airway epithelial cells. PHet successfully pinpointed the basal cell subtype associated with this phenomenon, a distinction that pre-annotated markers and dispersion-based features failed to make due to their admixed feature expression profiles. These findings underscore the potential of our method to deepen our understanding of the mechanisms underlying diseases and cell differentiation and contribute significantly to personalized medicine.
TDbasedUFE and TDbasedUFEadv: bioconductor packages to perform tensor decomposition based unsupervised feature extraction
Authors: Taguchi Y-h. , Turki Turki
Published: May 2023

Motivation

Tensor decomposition (TD) based unsupervised feature extraction (FE) was proposed almost five years ago and has been successfully applied to a wide range of bioinformatics problems ranging from biomarker identification to the identification of disease-causing genes and drug repositioning. Despite its successful applications, the use of TD-based unsupervised FE was not widely accepted because of the unpopularity of TD in this field.

Results

To overcome this difficulty, we developed two bioconductor packages, TDbasedUFE and TDbasedUFEadv. Using these two packages, all researchers who are not familiar with the concept of TD can make use of TD-based unsupervised FE for their purposes. When the performances of two specific functions, identification of differentially expressed genes and multiomics analysis, are implemented in TDbasedUFE and compared with those of two state-of-the-art (SOTA) methods (i.e., DESeq2 and DIABLO), TDbasedUFE can outperform these two SOTAs.

Availability and implementation

TDbasedUFE and TDbasedUFEadv are freely available as R/Bioconductor packages hosted athttps://bioconductor.org/packages/TDbasedUFEandhttps://bioconductor.org/packages/TDbasedUFEadv, respectively.
Genome-wide CRISPRi knockdown to map gene essentiality landscape in coliphages λ and P1
Authors: Piya Denish , Nolan Nicholas , Moore Madeline L. , Ramirez Hernandez Luis A. , Cress Brady F. , Young Ry , Arkin Adam P. , Mutalik Vivek K.
Published: May 2023

Phages are one of the key ecological drivers of microbial community dynamics, function and evolution. Despite their importance in bacterial ecology and evolutionary processes, phage genes are poorly characterized, hampering their usage in a variety of biotechnological applications. Methods to characterize such genes, even those critical to the phage life cycle, are labor-intensive and are generally phage-specific. Here, we develop a systematic gene essentiality mapping method scalable to new phage-host combinations that facilitate the identification of non-essential genes. As proof of concept, we use a catalytically inactive Cas12a mediated genome-wide CRISPRi assay to determine the essential genes in the canonical coliphages λ and P1. Results from a single panel of CRISPRi probes largely recapitulate the essential gene roster determined from decades of genetic analysis for lambda and provide new insights into essential and nonessential loci in P1. We present evidence of how CRISPRi polarity can lead to false positive gene essentiality assignments and recommend caution towards interpreting CRISPRi data on gene essentiality when applied to less studied phages. Finally, we show that we can engineer phages by inserting DNA barcodes into newly identified inessential regions, which will empower processes of identification, quantification and tracking of phages in diverse applications.