bluuebunny/crossref_metadata_2025 huggingface dataset:
Phyllosphere to Ferment: Site Conditions Structure Cacao Pod and Fermentation Microbiomes in Hawaiʻi
Authors: Lewis Ricky W. , Bittenbender Harry C. , Heisey Steven , Nguyen Nhu H.
Published: September 2023

Microbial fermentation is crucial to the development of flavors in cacao-based products, but how the abiotic environment and pod surface microbiomes can contribute to these different sensory profiles is underdeveloped. To better understand the connections between environment, plant variety, associated pod phyllosphere microbiomes, and the fermentation microbiome, we characterized the fungi and bacteria on pod surfaces and early fermentations of two cacao varieties across wet and dry sites on the island of O‘ahu, Hawai‘i. We showed that site (and the environmental conditions linked to those sites) significantly influenced the microbiomes of both the pod phyllosphere and fermentations but did not significantly explain the differences between cacao varieties. Certain taxa of bacteria and fungi seemingly prefer the wet Kualoa Ranch site compared with the drier Urban Garden Center Site. Rare members of the pod phyllosphere communities became highly enriched during fermentation, where basidiomycetous yeasts ( Filobasidium sp., Hannaella zeae, Rhodotorula mucilaginosa, R. paludigena, and Sporobolomyces carnicolor) became dominant at the wet site, and both ascomycetous and basidiomycetous yeasts ( Hyphopichia burtonii, Meyerozyma sp., Yamadazyma phyllophila, Filobasidium sp., Kwoniella heveanensis, R. mucilaginosa, Sporobolomyces sp., and S. carnicolor) became dominant at the dry site. The agricultural production site where cacao plants are grown should be considered carefully because it is likely important in structuring microbes that are present on pod surfaces and the microbes (mostly yeasts) that will be carried forward into fermentation. These yeasts may contribute to the development of the unique fruity or floral flavors in chocolates produced in Hawai‘i.

[Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
Distinct SAP102 and PSD-95 nano-organization defines multiple types of synaptic scaffold protein domains at single synapses
Authors: Metzbower Sarah R. , Dharmasri Poorna A. , Levy Aaron D. , Anderson Michael C. , Blanpied Thomas A.
Published: September 2023

The MAGUK family of scaffold proteins plays a central role in maintaining and modulating synaptic signaling, providing a framework to retain and position receptors, signaling molecules, and other synaptic components. Of these scaffold proteins, SAP102 and PSD-95 are essential for synaptic function at distinct developmental timepoints and perform overlapping as well as unique roles. While their similar structures allow for common binding partners, SAP102 is expressed earlier in synapse development and is required for synaptogenesis, whereas PSD-95 expression peaks later in development and is associated with synapse maturation. PSD-95 and other key synaptic proteins organize into subsynaptic nanodomains that have a significant impact on synaptic transmission, but the nanoscale organization of SAP102 is unknown. How SAP102 is organized within the synapse, and how it relates spatially to PSD-95 on a nanometer scale, could impact how SAP102 clusters synaptic proteins and underlie its ability to perform its unique functions. Here we used DNA-PAINT super-resolution microscopy to measure SAP102 nano-organization and its spatial relationship to PSD-95 at individual synapses. We found that like PSD-95, SAP102 accumulates in high-density subsynaptic nanoclusters. However, SAP102 nanoclusters were smaller and denser than PSD-95 nanoclusters across development. Additionally, only a subset of SAP102 nanoclusters co-organized with PSD-95, revealing that within individual synapses there are nanodomains that contain either one or both proteins. This organization into both shared and distinct subsynaptic nanodomains may underlie the ability of SAP102 and PSD-95 to perform both common and unique synaptic functions.

Significance statement

SAP102 and PSD-95 are two key members of the MAGUK family of synaptic scaffold proteins that are critical for synapse development, maintenance, and modification during plasticity. Because PSD-95 has a highly complex subsynaptic nanostructure that impacts synaptic function, we asked if SAP102 is similarly organized into nanoclusters at individual synapses and how it relates to PSD-95 within synapses. We found that SAP102 forms subsynaptic nanoclusters with unique properties, and that within individual synapses proteins both concentrate into overlapping nanodomains, as well as form MAGUK-specific nanodomains. This demonstrates that organization of synaptic proteins into nanoclusters is likely to be maintained within the family of MAGUK proteins and reveals potential mechanism for specializing functions within individual synapses based on scaffold protein nanodomains.
Antibiotic ResistantCampylobacterspp Isolated from Live Broilers at an Abattoir in Lusaka, Zambia
Authors: Mukupa John , Ndashe Kunda , Kabwali Emmanuel , Mwanza Grace , Mumba Bernadette
Published: September 2023

Antibiotic resistantCampylobacterspp causing campylobacteriosis continue to cause challenges in treatment of the infection. Poultry remains the main source of the foodborne disease. This study was undertaken to isolate and identify antibiotic resistantCampylobacterspp.

A total of 160 cloacal swabs were taken from broilers at a poultry abattoir in Lusaka. The samples were analyzed using standard bacteriological test. Antimicrobial susceptibility test was conducted following Clinical and Laboratory Standard Institute guideline and three antibiotics were used ciprofloxacin, tetracycline and erythromycin.

Results indicated thatCampylobacterspp was isolated from 18.75% of the sample population, furthermore the isolates were resistant to erythromycin and tetracycline and susceptible to ciprofloxacin. The results highlight the growing concern of poultry being a source of multi-drug resistant pathogenic bacteria.
Glucocorticoid receptor activation induces NK cells to produce AREG and restricts their anti-tumor activity in skin cancer
Authors: Wei Qin , Liang Guirong , zeng Rui , Li Yuancheng , Hong Anlan , Wang Hongsheng , Feng Suying , Wang Yan , Wang Yetao
Published: September 2023

Natural killer (NK) cells are recognized as powerful anti-tumor effector cells, but their efficacy is often hindered by the tumor microenvironment (TME). In this study, we analyzed the single-cell transcriptome and cytokine production profiles of NK cells from 24 and 68 paired peri-tumor and tumor skin tissues, respectively. We found that NK cells within skin tumors downregulated anti-tumor cytokines IFN-γ and TNF-α while upregulating amphiregulin (AREG), an EGFR ligand that promotes tumor growth and immune tolerance. This cytokine shift was linked to increased activity of the glucocorticoid receptor (GR, encoded by NR3C1). We further demonstrated that glucocorticoids acting as natural ligands, specifically induced AREG production in NK cells, while NR3C1 knockout and its inhibitors abolished this effect. PGE2, prevalent in TMEs, promoted AREG production independently of glucocorticoid dosage. Moreover, GR activation induced a memory response in NK cells, enhancing AREG production upon subsequent stimuli by increasing chromatin accessibility around the AREG promoter. AREG knockout NK cells exhibited significantly enhanced tumor suppression in NCG mice inoculated with human melanoma or cutaneous squamous cell carcinoma cells. These findings highlight the therapeutic potential of targeting AREG production in NK cells for cancer treatment.

Graphical abstract
Assessing the impact of transcriptomics data analysis pipelines on downstream functional enrichment results
Authors: Paton Victor , Gabor Attila , Flores Ricardo Omar Ramirez , Badia-i-Mompel Pau , Tanevski Jovan , Garrido-Rodriguez Martin , Saez-Rodriguez Julio
Published: September 2023

Transcriptomics, and in particular RNA-Seq, has become a widely used approach to assess the molecular state of biological systems. To facilitate its analysis, many tools have been developed for different steps, such as filtering lowly expressed genes, normalisation, differential expression, and enrichment. While numerous studies have examined the impact of method choices on differential expression results, little attention has been paid to their effects on further downstream functional analysis using enrichment of gene sets, such as pathways, which typically provides the basis for interpretation and follow-up experiments. To address this gap, we introduce FLOP (FunctionaL Omics Processing), a comprehensive nextflow-based workflow that combines various methods for preprocessing and downstream enrichment analysis, allowing users to perform end-to-end analyses of count level transcriptomic data. We illustrate FLOP capabilities on diverse datasets comprising samples from end-stage heart failure patients and cancer cell lines in both basal and drug-perturbed states. We found that the correlation between gene set enrichment analysis results can vary significantly for alternative pipelines. Additionally, we observed that not filtering the data had the highest impact on the correlation between pipelines in the gene set space, especially in settings with limited statistical power. Overall, our results underscore the impact of carefully evaluating the consequences of the choice of preprocessing methods on downstream enrichment analyses. We envision FLOP as a valuable tool to measure the robustness of functional analyses, ultimately leading to more reliable and conclusive biological findings.

Graphical abstract
Cell context-specific Synthetic lethality Prediction and Mechanism Analysis
Authors: Xing Yucui , Pu Mengchen , Cheng Kaiyang , Tian Kai , Wei Lanying , Zheng Weisheng , Peng Gongxin , Zhou Jielong , Zhang Yingsheng
Published: September 2023

Synthetic lethality (SL) holds significant promise as a targeted cancer therapy by selectively eliminating tumor cells while sparing normal cells. However, the discovery of SL gene pairs has encountered tremendous challenges, including high costs and low efficiency of experimental methods. Current computational approaches only provide limited insights because of overlooking the crucial aspects of cellular context dependency and mechanistic understanding of SL pairs. To overcome these challenges, we have developed SLWise, a deep-learning model capable of predicting SL interactions in diverse cellular backgrounds. We evaluated SLWise using a real world ground truth standard. The evaluation demonstrated that SLWise outperformed benchmark models in SL prediction. Additionally, we proposed a novel analysis scheme called SLAD-CE (SyntheticLethalAssociated GeneDetection andCell DamageEvaluation) for the identification of abnormal essential genes induced by SL gene pairs and tracking the extent of cell damage. Leveraging the cell-line-specific input feature L1000 and employing Gene Set Enrichment Analysis (GSEA), SLAD-CE provides valuable insights into the underlying mechanisms of SLWise-predicted gene pairs. The combined utilization of SLWise and SLAD-CE offers an approach for predicting and analyzing SL interactions in specific cellular contexts. Our findings highlight the potential of SLWise and SLAD-CE in advancing SL-based therapies by improving prediction accuracy and enhancing mechanistic understanding, ultimately contributing to the development of effective precision treatments for cancer.
Altered enhancer-promoter interaction leads toMNX1expression in pediatric acute myeloid leukemia with t(7;12)(q36;p13)
Authors: Weichenhan Dieter , Riedel Anna , Sollier Etienne , Toprak Umut H. , Hey Joschka , Breuer Kersten , Wierzbinska Justyna A. , Touzart Aurore , Lutsik Pavlo , Bähr Marion , Östlund Anders , Nilsson Tina , Jacobsson Susanna , Edler Marcel , Waraky Ahmed , Behrens Yvonne Lisa , Göhring Gudrun , Schlegelberger Brigitte , Steinek Clemens , Harz Hartmann , Leonhardt Heinrich , Dolnik Anna , Reinhard Dirk , Bullinger Lars , Palmqvist Lars , Lipka Daniel B. , Plass Christoph
Published: September 2023

Acute myeloid leukemia (AML) with the t(7;12)(q36;p13) translocation occurs only in very young children and has a poor clinical outcome. The expected oncofusion between breakpoint partners (MNX1andETV6) has only been reported in a subset of cases. However, a universal feature is the strong transcript and protein expression of MNX1, a homeobox transcription factor that is normally not expressed in hematopoietic cells. Here, we map the translocation breakpoints on chromosomes 7 and 12 in affected patients to a region proximal toMNX1and either introns 1 or 2 ofETV6. The frequency ofMNX1overexpression in pediatric AML (n=1556, own and published data) is 2.4% and occurs predominantly in t(7;12)(q36;p13) AML. Chromatin interaction assays in a t(7;12)(q36;p13) iPSC cell line model unravel an enhancer-hijacking event that explainsMNX1overexpression in hematopoietic cells. Our data suggest that enhancer-hijacking is a more common and overlooked mechanism for structural rearrangement-mediated gene activation in AML.

Key points

Expression analysis of over 1500 pediatric AML samples demonstratesMNX1expression as a universal feature of t(7;12)(q36;p13) AML as well as in rare cases without t(7;12)(q36;p13)

MNX1is activated by an enhancer-hijacking event in t(7;12)(q36;p13) AML and not, as previously postulated, by the creation of aMNX1::ETV6oncofusion gene.
Enzyme promiscuous profiles for protein sequence and reaction annotation
Authors: MohammadiPeyhani Homa , Sveshnikova Anastasia , Miskovic Ljubisa , Hatzimanikatis Vassily
Published: September 2023

1.1

Novel sequencing techniques and biochemical pathway prediction resources provide a wealth of data on novel proteins and computationally predicted enzymatic reactions. Accurate matching of protein sequences to enzymatic activities is crucial for advancing synthetic biology and metabolic engineering efforts. Here we present BridgIT+, a computational workflow that accounts for enzyme promiscuity and accurately predicts protein-reaction and reaction-protein associations. BridgIT+ builds upon the promiscuity-based method for annotating orphan and novel reactions with enzymatic activities, BridgIT, and utilizes position-specific scoring matrices (PSSM). The framework uses sequence alignment and enzyme promiscuity predictions to analyze protein sequences, identify sequence patterns, and create promiscuous protein sequence profiles for each reaction. These profiles allow us to predict the protein sequences most likely involved in the reaction. We showcase BridgIT+ by annotating (i) computationally predicted reactions with proteins and (ii) unannotated proteins ofE. coliproteome with enzymatic functions. We demonstrated the performance of BridgIT+ on several biochemical assays and compared it to three current state-of-the-art methods for matching proteins and reactions. We anticipate that the proposed conceptual framework will enhance our understanding of gene-protein-reaction relations and advance biological sequence and reaction annotation in biology and synthetic biology studies.
Measuring, visualizing and diagnosing reference bias with biastools
Authors: Lin Mao-Jan , Iyer Sheila , Chen Nae-Chyun , Langmead Ben
Published: September 2023

Many bioinformatics methods seek to reduce reference bias, but no methods exist to comprehensively measure it.Biastoolsanalyzes and categorizes instances of reference bias. It works in various scenarios, i.e. (a) when the donor’s variants are known and reads are simulated, (b) when donor variants are known and reads are real, and (c) when variants are unknown and reads are real. Usingbiastools, we observe that more inclusive graph genomes result in fewer biased sites. We find that end-to-end alignment reduces bias at indels relative to local aligners. Finally, we usebiastoolsto characterize how T2T references improve large-scale bias.
Elastin-derived peptides favor type 2 innate lymphoid cells in COPD
Authors: Lahire Sarah , Fichel Caroline , Rubaszewski Océane , Lerévérend Cédric , Audonnet Sandra , Visneux Vincent , Perotin Jeanne-Marie , Deslée Gaëtan , Le Jan Sébastien , Potteaux Stéphane , Le Naour Richard , Pommier Arnaud
Published: September 2023

Chronic obstructive pulmonary disease (COPD) is a condition characterized by chronic airway inflammation and obstruction, primarily caused by tobacco smoking. Although the involvement of immune cells in COPD pathogenesis is well established, the contribution of innate lymphoid cells (ILC) remains poorly understood. ILC are a type of innate immune cells that participate in tissue remodeling processes, but their specific role in COPD has not been fully elucidated. During COPD, the breakdown of pulmonary elastin generates elastin peptides that elicit biological activities on immune cells. This study aimed to investigate the presence of ILC in COPD patients and examine the impact of elastin peptides on their functionality.

Our findings revealed an elevated proportion of ILC2 in the peripheral blood of COPD patients, and a general activation of ILC as indicated by an increase in their cytokine secretion capacity. Notably, our study demonstrated that serum from COPD patients promotes ILC2 phenotype, likely due to the elevated concentration of IL-5, a cytokine known to favor ILC2 activation. Furthermore, we uncovered that this increase in IL-5 secretion is partially attributed to its secretion by macrophages upon stimulation by elastin peptides, suggesting an indirect role of elastin peptides on ILC in COPD.

These findings shed light on the involvement of ILC in COPD and provide insights into the potential interplay between elastin breakdown, immune cells, and disease progression. Further understanding of the mechanisms underlying ILC activation and their interaction with elastin peptides could contribute to the development of novel therapeutic strategies for COPD management.
Comparative analysis of metabolic models of microbial communities reconstructed from automated tools and consensus approaches
Authors: Hsieh Yunli Eric , Tandon Kshitij , Verbruggen Heroen , Nikoloski Zoran
Published: September 2023

Genome-scale metabolic models (GEMs) of microbial communities offer valuable insights into the functional capabilities of their members and facilitate the exploration of microbial interactions. These models are generated using different automated reconstruction tools, each relying on different biochemical databases that may affect the conclusions drawn from thein silicoanalysis. One way to address this problem is to employ a consensus reconstruction method that combines the outcomes of different reconstruction tools. Here, we conducted a comparative analysis of community models reconstructed from three automated tools, i.e. CarveMe, gapseq, and KBase, alongside a consensus approach, utilizing data from two marine bacterial communities. Our analysis revealed that these reconstruction approaches, while based on the same genomes, resulted in GEMs with varying numbers of genes and reactions as well as metabolic functionalities, attributed to the different databases employed. Further, our results indicated that the set of exchanged metabolites was more influenced by the reconstruction approach rather than the specific bacterial community investigated. This observation suggests a potential bias in predicting metabolite interactions using community GEMs. We also showed that consensus models encompassed a larger number of reactions and metabolites while concurrently reducing the presence of dead-end metabolites. Therefore, the usage of consensus models allows making full and unbiased use from aggregating genes from the different reconstructions in assessing the functional potential of metabolic communities.

Importance

Our study contributes significantly to the field of microbial community modeling through a comprehensive comparison of genome-scale metabolic models (GEMs) generated via various automated tools, including: CarveMe, gapseq, KBase, and a consensus approach. We revealed substantial structural disparities in model outcomes, primarily attributed to variations in the employed databases. A key finding underscored the substantial impact of the reconstruction approach on the set of exchanged metabolites, emphasizing the necessity for enhanced data integration strategies. The consensus models emerge as a powerful solution, exhibiting improved functional capabilities by encompassing a greater number of reactions, metabolites, and genes. This not only offers a more comprehensive representation of metabolic networks within bacterial communities but also shows promise in reducing variability for more accurate predictions of exchange metabolites. Overall, our research provides a critical framework for refining microbial community simulations, impacting fields from ecology to synthetic biology.
eDAVE - extension of GDC Data Analysis, Visualization, and Exploration Tools
Authors: Bińkowski Jan , Taryma-Leśniak Olga , Sokolowska Katarzyna Ewa , Przybylowicz Patrycja Kamila , Staszewski Melanie , Wojdacz Tomasz Kazimierz
Published: September 2023

Publicly available repositories such as Genomic Data Commons or Gene Expression Omnibus are a valuable research resource useful for hypothesis driven research as well as validation of the results of new experiments. Unfortunately, frequently advanced computational skills are required to mine those repositories making the use of those opulent research resources challenging, especially for researchers without bioinformatics expertise. To address this challenge, we have developed eDAVE, a user-friendly, web and desktop interface enabling intuitive and robust analysis of almost 12 000 methylomes and transcriptomes from over 200 types of cells and tissues deposited in the Genomic Data Commons repository.

Web app implemented in Python, is supported for major browsers and available at:https://edave.pum.edu.pl/
Global impact of aberrant splicing on human gene expression levels
Authors: Fair Benjamin , Abad Najar Carlos Buen , Zhao Junxing , Lozano Stephanie , Reilly Austin , Mossian Gabriela , Staley Jonathan P , Wang Jingxin , Li Yang I
Published: September 2023

Alternative splicing (AS) is pervasive in human genes, yet the specific function of most AS events remains unknown. It is widely assumed that the primary function of AS is to diversify the proteome, however AS can also influence gene expression levels by producing transcripts rapidly degraded by nonsense-mediated decay (NMD). Currently, there are no precise estimates for how often the coupling of AS and NMD (AS-NMD) impacts gene expression levels because rapidly degraded NMD transcripts are challenging to capture. To better understand the impact of AS on gene expression levels, we analyzed population-scale genomic data in lymphoblastoid cell lines across eight molecular assays that capture gene regulation before, during, and after transcription and cytoplasmic decay. Sequencing nascent mRNA transcripts revealed frequent aberrant splicing of human introns, which results in remarkably high levels of mRNA transcripts subject to NMD. We estimate that ∼15% of all protein-coding transcripts are degraded by NMD, and this estimate increases to nearly half of all transcripts for lowly-expressed genes with many introns. Leveraging genetic variation across cell lines, we find that GWAS trait-associated loci explained by AS are similarly likely to associate with NMD-induced expression level differences as with differences in protein isoform usage. Additionally, we used the splice-switching drug risdiplam to perturb AS at hundreds of genes, finding that ∼3/4 of the splicing perturbations induce NMD. Thus, we conclude that AS-NMD substantially impacts the expression levels of most human genes. Our work further suggests that much of the molecular impact of AS is mediated by changes in protein expression levels rather than diversification of the proteome.
Synergistic anti-tumor activity, reduced pERK, and immuno-stimulatory cytokine profiles with 5-FU or ONC212 plus KRAS G12D inhibitor MRTX1133 in CRC and pancreatic cancer cells independent of G12D mutation
Authors: Tajiknia Vida , Pinho-Schwermann Maximilian , Srinivasan Praveen R. , Hernandez Borrero Liz , Zhang Leiqing , Huntington Kelsey E. , El-Deiry Wafik S.
Published: September 2023

KRAS mutations occur in ∼40-50% of mCRC and are associated with aggressive disease that is refractory to anti-EGFR therapies. Pancreatic cancer harbors ∼90% KRAS driver gene mutation frequency. Small molecules targeting KRAS G12C gained FDA approval for KRAS G12C-mutated NSCLC. ONC212, a fluorinated imipridone with nM anti-cancer activity has preclinical efficacy against pancreatic cancer and other malignancies. MRTX1133, identified as a noncovalent selective KRAS G12D inhibitor that suppresses G12D signaling by binding to the switch II pocket thereby inhibiting protein-protein interactions. We investigated cell viability, drug synergies, pERK suppression and cytokine, chemokine or growth factor alterations following treatment with 5-Fluorouracil (5-FU) or ONC212 plus MRTX1133 in 6 human CRC and 4 human pancreatic cancer cell lines. IC50 sensitivities ranged from 7 to 12 μM for 5-FU, 0.2-0.8 μM for ONC212, and >100 nM to >5,000 nM for MRTX1133 (G12D N=4: LS513 >100, HPAF-II >1,000, SNUC2B >5,000, PANC-1 >5,000). For non-G12D, the range of IC50 for MRTX1133 was >1,000 to >5,000 nM for CRC lines with G12V, G13D, or WT KRAS (N=7). Synergies between MRTX1133 plus 5-FU or ONC212 were observed regardless of KRAS G12D mutation with combination indices of <0.5 indicating strong synergy. Observed synergies were greater with MRTX1133 plus ONC212 compared to MRTX1133 plus 5-FU. pERK was suppressed with mutant but not wild-type KRAS at nM MRTX1133 doses. Immunostimulatory profiles included reduction in IL8/CXCL8, MICA, Angiopoietin 2, VEGF and TNF-alpha and increase in IL-18/IL-1F4 with MRTX treatments and combinations. Our studies reveal preclinical activity of MRTX1133 alone or synergies when combined with 5-FU or ONC212 against mCRC and pancreatic cancer cells regardless of KRAS G12D mutation. The results suggest that KRAS G12V and KRAS G13D should be further considered in clinical trials including combination therapies involving MRTX1133 and 5-FU or ONC212.
A phylogenomic approach, combined with morphological characters gleaned via machine learning, uncovers the hybrid origin and biogeographic diversification of the plum genus
Authors: Hodel Richard G. J. , Winslow Sundre K. , Liu Bin-Bin , Johnson Gabriel , Trizna Michael , White Alex E. , Dikow Rebecca B. , Potter Daniel , Zimmer Elizabeth A. , Wen Jun
Published: September 2023

The evolutionary histories of species have been shaped by genomic, environmental, and morphological variation. Understanding the interactions among these sources of variation is critical to infer accurately the biogeographic history of lineages. Here, using the geographically widely distributed plum genus (Prunus, Rosaceae) as a model, we investigate how changes in genomic and environmental variation drove the diversification of this group, and we quantify the morphological features that facilitated or resulted from diversification. We sequenced 610 nuclear loci and complete chloroplast genomes from 75 species representing all major lineages inPrunus, with a special focus on the understudied tropical racemose group. The environmental variation in extant species was quantified by synthesizing bioclimatic variables into principal components of environmental variation using thousands of georeferenced herbarium specimens. We used machine learning algorithms to classify and measure morphological variation present in thousands of digitized herbarium sheet images. Our phylogenomic and biogeographic analyses revealed that ancient hybridization and/or allopolyploidy spurred the initial rapid diversification of the genus in the early Eocene, with subsequent diversification in the north temperate zone, Neotropics, and Paleotropics. This diversification involved successful transitions between tropical and temperate biomes, an exceedingly rare event in woody plant lineages, accompanied by morphological changes in leaf and reproductive morphology. The machine learning approach detected morphological variation associated with ancient hybridization and quantified the breadth of morphospace occupied by major lineages within the genus. The paleotropical lineages ofPrunushave diversified steadily since the late Eocene/early Oligocene, while the neotropical lineages diversified much later. Critically, both the tropical and temperate lineages have continued to diversify. We conclude that the genomic rearrangements created by reticulation deep in the phylogeny ofPrunusmay explain why this group has been more successful than other groups with tropical origins that currently persist only in either tropical or temperate regions, but not both.
Plasma cell differentiation, antibody quality, and initial germinal center B cell population depend on glucose influx rate
Authors: Brookens Shawna K. , Cho Sung Hoon , Paik Yeeun , Meyer Kaylor , Raybuck Ariel L. , Park Chloe , Greenwood Dalton L. , Rathmell Jeffrey C. , Boothby Mark R.
Published: September 2023

Antibody secretion into sera, selection for higher affinity BCR, and the generation of higher Ab affinities are important elements of immune response optimization, and a core function of germinal center reactions. B cell proliferation requires nutrients to support the anabolism inherent in clonal expansion. Glucose usage by GC B cells has been reported to contribute little to their energy needs, with questions raised as to whether or not glucose uptake or glycolysis increases in GC B cells compared to their naïve precursors. Indeed, metabolism can be highly flexible, such that supply shortage along one pathway may be compensated by increased flux on others. We now show that elimination of the glucose transporter GLUT1 after establishment of a pre-immune B cell repertoire, even after initiation of the GC B cell gene expression program, decreased initial GC B cell population numbers, affinity maturation, and PC outputs. Glucose oxidation was heightened in GC B cells, but this hexose flowed more into the pentose phosphate pathway (PPP), whose activity was important in controlling reactive oxygen (ROS) and ASC production. In modeling how glucose usage by B cells promotes the Ab response, the control of ROS appeared insufficient. Surprisingly, the combination of galactose, which mitigated ROS, with provision of mannose - an efficient precursor to glycosylation - supported robust production of and normal Ab secretion by ASC under glucose-free conditions. Collectively, the findings indicate that GC depend on normal glucose influx, especially in PC production, but reveal an unexpected metabolic flexibility in hexose requirements.

KEY POINTS

Glucose influx is critical for GC homeostasis, affinity maturation and the generation of Ab-secreting cells.

Plasma cell development uses the Pentose Phosphate Pathway, and hexose sugars maintain redox homeostasis.

PCs can develop and achieve robust Ab secretion in the absence of glucose using a combination of hexose alternatives.
Computational Assessment of Aromatase: Unmasking Therapeutic Avenues for Female Hormonal Disorders
Authors: Koirala Sandesh P. , Magar Bhawana S. , Yadav Amit K. , Regmi Anisha , Pokharel Aashish , Subedi Samiran , Aryal Pramod
Published: September 2023

Women of reproductive age widely experience the physical, mental, and emotional effects of hormonal imbalances. The levels of two hormones, estrogen, and progesterone, were particularly high. When these two hormones are unbalanced, symptoms such as irregular menstrual cycles, pelvic pain, and uterine fibroids can appear. Statistics show that 80 percent of women have hormonal imbalances. The creation of novel disease-containing drug candidates may be facilitated by computer-aided drug design (CADD), as many drugs and surgical treatments have unique adverse effects. Achieving good data coverage requires an optimized process for protein identification and enhanced selection techniques for medicinal compounds, including their metabolic characterization. In this study, aromatase is the prioritized protein that acted as a rate-limiting enzyme in steroidogenesis. To maintain its expression and regulation to control estrogen production, natural compounds were retrieved from the ZINC15 database through ADME/TOX property filtration. Compound B, specifically designated as (1R,3S,6S,7S,10S,11R)-7-[(dimethylamino)methyl]-3,12-dimethyl-2,9-dioxatetracyclo [9.3.0.01,3.06,10] tetradec-12-en-8-one, exhibits remarkable therapeutic potential, as evidenced by its inability to inhibit S-adenosyl methionine (SAM) biosynthesis, the observed stability of molecular interactions based on Density Functional Theory (DFT), and a favorable energy gap between molecular orbital stages. This research can be employed as a utility module for fast screening of drug-like molecules and taking these leads forward to clinical trials, assessing their value as potential suitors for drug repurposing against female hormonal disorders.
RapTCR: Rapid exploration and visualization of T-cell receptor repertoires
Authors: Van Deuren Vincent M.L. , Valkiers Sebastiaan , Laukens Kris , Meysman Pieter
Published: September 2023

Abstract

Motivation

The acquisition of T-cell receptor (TCR) repertoire sequence data has become faster and cheaper due to advancements in high-throughput sequencing. However, fully exploiting the diagnostic and clinical potential within these TCR repertoires requires a thorough understanding of the inherent repertoire structure. Hence, visualizing the full space of TCR sequences could be a key step towards enabling exploratory analysis of TCR repertoire, driving their enhanced interrogation. Nonetheless, current methods remain limited to rough profiling of TCR V and J gene distributions. Addressing this need, we developed RapTCR, a tool for rapid visualization and post-analysis of TCR repertoires.

Approach

To overcome computational complexity, RapTCR introduces a novel, simple embedding strategy that represents TCR amino acid sequences as short vectors while retaining their pairwise alignment similarity. RapTCR then applies efficient algorithms for indexing these vectors and constructing their nearest neighbor network. It provides multiple visualization options to map and interactively explore a TCR network as a two-dimensional representation. Benchmarking analyses using epitope-annotated datasets demonstrate that these RapTCR visualizations capture TCR similarity features on a global level (e.g., J gene) and locally (e.g., epitope reactivity). RapTCR is available as a Python package, implementing the intuitive scikit-learn syntax to easily generate insightful, publication-ready figures for TCR repertoires of any size.

Availability and Implementation

RapTCR was written in Python 3. It is available as an anaconda package (https://anaconda.org/vincentvandeuren/raptcr), and on github (https://github.com/vincentvandeuren/RapTCR). Documentation and example notebooks are available at vincentvandeuren.github.io/rapTCR_docs/.

Contact

pieter.meysman@uantwerpen.be
Signatures of transposon-mediated genome inflation, host specialization, and photoentrainment inEntomophthora muscaeand allied entomophthoralean fungi
Authors: Stajich Jason E. , Lovett Brian , Lee Emily , Macias Angie M. , Hajek Ann E. , de Bivort Benjamin L. , Kasson Matt T. , De Fine Licht Henrik H. , Elya Carolyn
Published: September 2023

Despite over a century of observations, the obligate insect parasites within the order Entomophthorales remain poorly characterized at the genetic level. This is in part due to their large genome sizes and difficulty in obtaining sequenceable material. In this manuscript, we leveraged a recently-isolated, laboratory-tractableEntomophthora muscaeisolate and improved long-read sequencing to obtain a largely-complete entomophthoralean genome. OurE. muscaeassembly is 1.03 Gb, consists of 7,810 contigs and contains 81.3% complete fungal BUSCOs. Using a comparative approach with other available (transcriptomic and genomic) datasets from entomophthoralean fungi, we provide new insight into the biology of these understudied pathogens. We offer a head-to-head comparison of morphological and molecular data for species within theE. muscaespecies complex. Our findings suggest that substantial taxonomic revision is needed to define species within this group and we provide recommendations for differentiating strains and species in the context of the existing body ofE. muscaescientific literature. We show that giant genomes are the norm within Entomophthoraceae owing to extensive, but not recent, Ty3 retrotransposon activity, despite the presence of machinery to defend against transposable elements(RNAi). In addition, we find thatE. muscaeand its closest allies are enriched for M16A peptidases and possess genes that are likely homologs to the blue-light sensorwhite-collar 1, aNeurospora crassagene that has a well-established role in maintaining circadian rhythms. We find thatE. muscaehas an expanded group of acid-trehalases, consistent with trehalose being the primary sugar component of fly (and insect) hemolymph. We uncover evidence thatE. muscaediverged from other entomophthoralean fungi by expansion of existing families, rather than loss of particular domains, and possesses a potentially unique suite of secreted catabolic enzymes, consistent withE. muscae’s species-specific, biotrophic lifestyle. Altogether, we provide a genetic and molecular foundation that we hope will provide a platform for the continued study of the unique biology of entomophthoralean fungi.
Native ultrastructure of fresh human brain vitrified directly from autopsy revealed by cryo-electron tomography with cryo-plasma focused ion beam milling
Authors: Creekmore Benjamin C. , Kixmoeller Kathryn , Black Ben E. , Lee Edward B. , Chang Yi-Wei
Published: September 2023

Ultrastructure of human brain tissue has traditionally been examined using electron microscopy (EM) following chemical fixation, staining, and mechanical sectioning, which limit attainable resolution and introduce artifacts. Alternatively, cryo-electron tomography (cryo-ET) offers the potential to image unfixed cellular samples at higher resolution while preserving their native structures, but it requires samples to be frozen free from crystalline ice and thin enough to image via transmission EM. Due to these requirements, cryo-ET has yet to be employed to investigate the native ultrastructure of unfixed, never previously frozen human brain tissue. Here we present a method for generating lamellae in human brain tissue obtained at time of autopsy that can be imaged via cryo-ET. We vitrify the tissue directly on cryo-EM grids via plunge-freezing, as opposed to high pressure freezing which is generally used for thick samples. Following vitrification, we use xenon plasma focused ion beam (FIB) milling to generate lamellae directly on-grid. In comparison to gallium FIB, which is commonly used for biological samples, xenon plasma FIB is powerful enough to efficiently mill large volume samples, such as human brain tissue. Additionally, our approach allows for lamellae to be generated at variable depth inside the tissue as opposed to being limited to starting at the surface of the tissue. Lamellae generated in Alzheimer’s disease brain tissue and imaged by cryo-ET reveal intact subcellular structures including components of autophagy and potential tau fibrils. Furthermore, we visualize myelin revealing intact compact myelin and functional cytoplasmic expansions such as cytoplasmic channels and the inner tongue. From these images we also measure the dimensions of myelin membranes, providing insight into how myelin basic protein forces out oligodendrocyte cytoplasm to form compact myelin and tightly links intracellular polar head groups of the oligodendrocyte plasma membrane. This approach provides a first view of unfixed, never previously frozen human brain tissue prepared by cryo-plasma FIB milling and imaged at high resolution by cryo-ET.
Multi-omic characterization of antibody-producing CHO cell lines elucidates metabolic reprogramming and nutrient uptake bottlenecks
Authors: Gopalakrishnan Saratram , Johnson William , Valderrama-Gomez Miguel A. , Icten Elcin , Tat Jasmine , Lay Fides , Diep Jonathan , Gomez Natalia , Stevens Jennitte , Schlegel Fabrice , Rolandi Pablo , Kontoravdi Cleo , Lewis Nathan
Published: September 2023

Characterizing the phenotypic diversity and metabolic capabilities of industrially relevant manufacturing cell lines is critical to bioprocess optimization and cell line development. Metabolic capabilities of the production hosts limit nutrient and resource channeling into desired cellular processes and can have a profound impact on productivity but cannot be directly inferred from measured data such as spent media concentrations or transcriptomics. Here, we present an integrated multi-omic characterization approach combining exo-metabolomics, transcriptomics, and genome-scale metabolic network analysis and apply it to three antibody-producing Chinese Hamster Ovary cell lines to reprogramming features associated with high-producer clones and metabolic bottlenecks limiting product production in an industrial bioprocess. Analysis of individual datatypes revealed a decreased nitrogenous byproduct secretion in high-producing clones and the topological changes in peripheral metabolic pathway expression associated with phase shifts. An integrated omics analysis in the context of the genome-scale metabolic model elucidated the differences in central metabolism and identified amino acid utilization bottlenecks limiting cell growth and antibody production that were not evident from exo-metabolomics or transcriptomics alone. Thus, we demonstrate the utility of a multi-omics characterization in providing an in-depth understanding of cellular metabolism, which is critical to efforts in cell engineering and bioprocess optimization.
Auranofin induces lethality driven by reactive oxygen species in high-grade serous ovarian cancer cells
Authors: Abdalbari Farah H. , Martinez-Jaramillo Elvis , Forgie Benjamin N. , Tran Estelle , Zorytcha Edith , Goyeneche Alicia A. , Telleria Carlos M.
Published: September 2023

High-grade serous ovarian cancer (HGSOC) accounts for 70% of ovarian cancer cases in the clinical setting; the survival rate for this disease remains remarkably low due to the lack of long-term consolidation therapies following the standard platinum-based chemotherapy, which is not long lasting as the disease recurs as platinum resistant. The purpose of this study was to explore a novel treatment against HGSOC using the gold complex auranofin (AF). AF primarily functions as a pro-oxidant agent through the inhibition of thioredoxin reductase (TrxR), an antioxidant enzyme that is overexpressed in ovarian cancer. We investigated the effect of AF on TrxR activity and various mechanisms of cytotoxicity using HGSOC cells that are clinically sensitive or resistant to platinum. In addition, we studied the interaction between AF and another pro-oxidant agent, L-buthionine sulfoximine (L-BSO), an anti-glutathione (GSH) compound. We demonstrate that AF potently inhibits TrxR activity and reduces the vitality and viability of HGSOC cells regardless of their sensitivities to platinum. We show that AF induces accumulation of reactive oxygen species (ROS), triggers the depolarization of the mitochondrial membrane, and kills HGSOC cells by inducing apoptosis. Yet, AF-induced cell death is abrogated by the ROS-scavenger N-acetyl cysteine (NAC). In addition, the lethality of AF is associated with the activation of caspases-3/7 and the generation of DNA damage, effects that are also prevented by the presence of NAC. Finally, when AF and L-BSO are combined, we observed a synergistic lethality against HGSOC cells, which is mediated by a further increase in ROS together with a decrease in the levels of the antioxidant GSH. In summary, our results support the concept that AF can be used alone or in combination with L-BSO to kill HGSOC cells regardless of their platinum sensitivities suggesting that depletion of antioxidants is an efficient route for treating this disease.
Circadian regulation ofMGMTexpression and promoter methylation underlies daily rhythms in TMZ sensitivity in glioblastoma
Authors: Gonzalez-Aponte Maria F. , Damato Anna R. , Trebucq Laura Lucía , Simon Tatiana , Cárdenas-García Sandra P. , Cho Kevin , Patti Gary J. , Golombek Diego A. , Chiesa Juan José , Herzog Erik D.
Published: September 2023

Background

Glioblastoma (GBM) is the most common primary brain tumor in adults. Despite extensive research and clinical trials, median survival post-treatment remains at 15 months. Thus, all opportunities to optimize current treatments and improve patient outcomes should be considered. A recent retrospective clinical study found that taking TMZ in the morning compared to the evening was associated with a 6-month increase in median survival in patients withMGMT-methylated GBM. Here, we hypothesized that TMZ efficacy depends on time-of-day and O6-Methylguanine-DNA Methyltransferase (MGMT) activity in murine and human models of GBM.

Methods and Results

In vitrorecordings using real-time bioluminescence reporters revealed that GBM cells have intrinsic circadian rhythms in the expression of the core circadian clock genesBmal1andPer2, as well as in the DNA repair enzyme,MGMT. Independent measures ofMGMTtranscript levels and promoter methylation also showed daily rhythms intrinsic to GBM cells. These cells were more susceptible to TMZ when delivered at the daily peak ofBmal1transcription. We found thatin vivomorning administration of TMZ also decreased tumor size and increased body weight compared to evening drug delivery in mice bearing GBM xenografts. Finally, inhibition of MGMT activity with O6-Benzylguanine abrogated the daily rhythm in sensitivity to TMZin vitroby increasing sensitivity at both the peak and trough ofBmal1expression.

Conclusion

We conclude that chemotherapy with TMZ can be dramatically enhanced by delivering at the daily maximum of tumorBmal1expression and minimum ofMGMTactivity.

Graphical Abstract
COSMIC-dFBA: A novel multi-scale hybrid framework for bioprocess modeling
Authors: Gopalakrishnan Saratram , Johnson William , Valderrama-Gomez Miguel A. , Icten Elcin , Tat Jasmine , Ingram Michael , Shek Coral Fung , Chan Pik K. , Schlegel Fabrice , Rolandi Pablo , Kontoravdi Cleo , Lewis Nathan
Published: September 2023

Metabolism governs cell performance in biomanufacturing, as it fuels growth and productivity. However, even in well-controlled culture systems, metabolism is dynamic, with shifting objectives and resources, thus limiting the predictive capability of mechanistic models for process design and optimization. Here, we present Cellular Objectives and State Modulation In bioreaCtors (COSMIC)-dFBA, a hybrid multi-scale modeling paradigm that accurately predicts cell density, antibody titer, and bioreactor metabolite concentration profiles. Using machine-learning, COSMIC-dFBA decomposes the instantaneous metabolite uptake and secretion rates in a bioreactor into weighted contributions from each cell state (growth or antibody-producing state) and integrates these with a genome-scale metabolic model. A major strength of COSMIC-dFBA is that it can be parameterized with only metabolite concentrations from spent media, although constraining the metabolic model with other omics data can further improve its capabilities. Using COSMIC-dFBA, we can predict the final cell density and antibody titer to within 10% of the measured data, and compared to a standard dFBA model, we found the framework showed a 90% and 72% improvement in cell density and antibody titer prediction, respectively. Thus, we demonstrate our hybrid modeling framework effectively captures cellular metabolism and expands the applicability of dFBA to model the dynamic conditions in a bioreactor.