Effective Control of Sclerotinia Stem Rot in Canola Plants Through Application of Exogenous Hairpin RNA of Multiple Sclerotinia sclerotiorum Genes.

Sclerotinia stem rot is a globally destructive plant disease caused by Sclerotinia sclerotiorum. Current management of Sclerotinia stem rot primarily relies on chemical fungicides and crop rotation, raising environmental concerns. In this study, we developed an eco-friendly RNA bio-fungicide targeting S. sclerotiorum. Six S. sclerotiorum genes were selected for double-stranded RNA (dsRNA) synthesis. Four genes, a chitin-binding domain, mitogen-activated protein kinase, oxaloacetate acetylhydrolase, and abhydrolase-3, were combined to express hairpin RNA in Escherichia coli HT115. The effect of application of total RNA extracted from E. coli HT115 expressing hairpin RNA on disease progressive and necrosis lesions was evaluated. Gene expression analysis using real-time PCR showed silencing of the target genes using 5 ng/µl of dsRNA in a fungal liquid culture. A detached leaf assay and greenhouse application of dsRNA on canola stem and leaves showed variation in the reduction of necrosis symptoms by dsRNA of different genes, with abhydrolase-3 being the most effective. The dsRNA from a combination of four genes reduced disease severity significantly (P = 0.01). Plants sprayed with hairpin RNA from four genes had lesions that were almost 30% smaller than those of plants treated with abhydrolase-3 alone, in lab and greenhouse assays. The results of this study highlight the potential of RNA interference to manage diseases caused by S. sclerotiorum; however, additional research is necessary to optimize its efficacy.

Detection and editing of the updated Arabidopsis plastid- and mitochondrial-encoded proteomes through PeptideAtlas.

Arabidopsis (Arabidopsis thaliana) ecotype Col-0 has plastid and mitochondrial genomes encoding over 100 proteins. Public databases (e.g. Araport11) have redundancy and discrepancies in gene identifiers for these organelle-encoded proteins. RNA editing results in changes to specific amino acid residues or creation of start and stop codons for many of these proteins, but the impact of RNA editing at the protein level is largely unexplored due to the complexities of detection. Here, we assembled the nonredundant set of identifiers, their correct protein sequences, and 452 predicted nonsynonymous editing sites of which 56 are edited at lower frequency. We then determined accumulation of edited and/or unedited proteoforms by searching ∼259 million raw tandem MS spectra from ProteomeXchange, which is part of PeptideAtlas (www.peptideatlas.org/builds/arabidopsis/). We identified all mitochondrial proteins and all except 3 plastid-encoded proteins (NdhG/Ndh6, PsbM, and Rps16), but no proteins predicted from the 4 ORFs were identified. We suggest that Rps16 and 3 of the ORFs are pseudogenes. Detection frequencies for each edit site and type of edit (e.g. S to L/F) were determined at the protein level, cross-referenced against the metadata (e.g. tissue), and evaluated for technical detection challenges. We detected 167 predicted edit sites at the proteome level. Minor frequency sites were edited at low frequency at the protein level except for cytochrome C biogenesis 382 at residue 124 (Ccb382-124). Major frequency sites (>50% editing of RNA) only accumulated in edited form (>98% to 100% edited) at the protein level, with the exception of Rpl5-22. We conclude that RNA editing for major editing sites is required for stable protein accumulation.

Detection of the Arabidopsis Proteome and Its Post-translational Modifications and the Nature of the Unobserved (Dark) Proteome in PeptideAtlas.

This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource (build 2023-10) providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected post-translational modifications (PTMs), and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18,267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins, and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome: the "dark" proteome. This dark proteome is highly enriched for E3 ligases, transcription factors, and for certain (e.g., CLE, IDA, PSY) but not other (e.g., THIONIN, CAP) signaling peptides families. A machine learning model trained on RNA expression data and protein properties predicts the probability that proteins will be detected. The model aids in discovery of proteins with short half-life (e.g., SIG1,3 and ERF-VII TFs) and for developing strategies to identify the missing proteins. PeptideAtlas is linked to TAIR, tracks in JBrowse, and several other community proteomics resources.

Exploring COX-2 inhibitors in tuberculosis: A whole-blood model approach for immune response and adjunt therapy evaluation.

Pulmonary tuberculosis (TB) inflammation is an underestimated disease complication which anti-inflammatory drugs may alleviate. This study explored the potential use of the COX-2 inhibitors acetylsalicylic acid (ASA) and celecoxib in 12 TB patients and 12 healthy controls using a whole-blood ex vivo model where TNFα, PGE2, and LTB4 plasma levels were quantitated by ELISA; we also measured COX-2, 5-LOX, 12-LOX, and 15-LOX gene expression. We observed a significant TNFα production in response to stimulation with LPS or M. tuberculosis (Mtb). Celecoxib, but not ASA, reduced TNFα and PGE2 production, while increasing LTB4 in patients after infection with Mtb. Gene expression of COX-2 and 5-LOX was higher in controls, while 12-LOX was significantly higher in patients. 15-LOX expression was similar in both groups. We concluded that COX-2 inhibitors downregulate inflammation after Mtb infection, and our methodology offers a straightforward time-efficient approach for evaluating different drugs in this context. Further research is warranted to elucidate the underlying mechanisms and assess the potential clinical benefit.

Serum pro-inflammatory biomarkers associated with improvement in quality of life in pulmonary tuberculosis.

Introduction: Pulmonary dysfunction is an underestimated complication in tuberculosis (TB) infection, affecting quality of life (QoL). Although respiratory function tests objectively reflect lung disturbances in a specific moment, predictors of illness severity at the time of diagnosis are still lacking. Methods: We measured serum pro-inflammatory cytokines (TNF-α and IL-8), eicosanoids (PGE2, LTB4, RvD1, Mar1, and LXA4), a marker of tissue damage (cell-free nucleosomes), and indicators of redox status (malonaldehyde, 8-isoprostane, total oxidants, and antioxidants), as well as a score of radiological abnormalities (SRA) and a QoL questionnaire, in 25 patients with pulmonary TB at the time of diagnosis (t0) and two months after the initiation of treatment (t2). Results: We found higher antioxidant levels in the patients with the worst QoL at t0, and all the indicators of the prooxidant state were significantly reduced at t2, while the total antioxidant levels increased. LTB4, a pro-inflammatory eicosanoid, was diminished at t2, while all the pro-resolutory lipids decreased substantially. Significant correlations between the SRA and the QoL scores were observed, the latter showing a substantial reduction at t2, ranking it as a reliable tool for monitoring disease evolution during TB treatment. Discussion: These results suggest that evaluating a combination of these markers might be a valuable predictor of QoL improvement and a treatment response indicator; in particular, the oxidation metabolites and eicosanoid ratios could also be proposed as a future target for adjuvant therapies to reduce inflammation-associated lung injury in TB disease.

First Report of Verticillium stripe of Canola Caused by Verticillium longisporum in North Dakota.

North Dakota leads the U.S.A. in canola (Brassica napus L.) production (5) and approximately one-third of the acreage is located in the northeastern portion of the state. A field survey conducted at the end of the 2021 growing season in northeastern North Dakota revealed the presence of a single field with approximately 15% plants exhibiting whitish discoloration symptoms in the lower third of the stems. The epidermis on the discolored areas was peeling, and the exposed tissues were dark grey to dark-brown. Stem samples taken to the laboratory were surface disinfested with a 5% aqueous solution of NaOCl for 60 sec and rinsed thrice with sterile water. Under aseptic conditions, small stem pieces were plated on V-8 medium amended with 150 mg each of penicillin and streptomycin per liter of medium and incubated at 22 oC under 16 h light daily. Under the microscope, conidiophores were verticillate, hyaline, and had three branches. Conidia were single-celled, hyaline, and measured on average 9.2 + 1.8 µm. Microsclerotia were irregularly shaped. These features match the description of Verticillium longisporum (Stark) Karapapa Bainbr. & Heale, (4). Genomic DNA was extracted from a single-spore culture of an isolate as described by Azizi et al. (1). PCR assays were conducted twice on two independent DNA samples extracted from the same isolate using V. longisporum species-specific primer set VlspF1 and VlspR4 (2) with denaturation at 95 oC for 3 min, followed by 35 cycles of amplification at 94 oC for 1 min then 56 oC for 30 sec and 72 oC for 1 min, followed by a final period at 72 oC for 5 min. The sequenced PCR product, which had 100% homology with GenBank V. longisporum reference samples KY704097 and HE972063, was assigned GenBank accession number OR088215. Pathogenicity tests were conducted in greenhouse. Briefly, twenty seeds of the canola cv. Westar were incubated on a sterilized wet paper towel for five days at 22 oC. The seedlings were carefully lifted, and their root tips cut with scissors. Ten wounded seedlings were immersed in a V. longisporum spore suspension with 2.07 x 106 spores per ml for 30 minutes and the other ten in distilled water (controls). The plants were transplanted into pots (10x10x13 cm) containing Sunshine Mix # 1 potting mix (Fison Horticulture, Vancouver, B. C.). The study was conducted twice, with individual plants as replications. Three weeks later, 20% of inoculated plants had died and at physiological maturity, the rest of them had stunted growth and blackened internal stem tissues while external stem symptoms resembled those found in the field. All control plants reached maturity without symptoms. The pathogen re-isolated from inoculated plants were morphologically identical to the one retrieved from the field. These results confirmed the isolate as Verticillium longisporum. This is the first report of Verticillium stripe on canola in the US. In North America, the disease was first reported in Manitoba, Canada, in 2014 but subsequent surveys showed it is widespread in Canada (3). Identification of genetic resistance against this disease is required to ameliorate the threat this disease represents to US canola production.

A Boolean network model of the double-strand break repair pathway choice.

Double strand break (DSB) repair is critical to maintaining the integrity of the genome. DSB repair deficiency underlies multiple pathologies, including cancer, chromosome instability syndromes, and, potentially, neurodevelopmental defects. DSB repair is mainly handled by two pathways: highly accurate homologous recombination (HR), which requires a sister chromatid for template-based repair, limited to S/G2 phases of the cell cycle, and canonical non-homologous end joining (c-NHEJ), available throughout the cell cycle in which minimum homology is sufficient for highly efficient yet error-prone repair. Some circumstances, such as cancer, require alternative highly mutagenic DSB repair pathways like microhomology-mediated end-joining (MMEJ) and single-strand annealing (SSA), which are triggered to attend to DNA damage. These non-canonical repair alternatives are emerging as prominent drivers of resistance in drug-based tumor therapies. Multiple DSB repair options require tight inter-pathway regulation to prevent unscheduled activities. In addition to this complexity, epigenetic modifications of the histones surrounding the DSB region are emerging as critical regulators of the DSB repair pathway choice. Modeling approaches to understanding DSBs repair pathway choice are advantageous to perform simulations and generate predictions on previously uncharacterized aspects of DSBs response. In this work, we present a Boolean network model of the DSB repair pathway choice that incorporates the knowledge, into a dynamic system, of the inter-pathways regulation involved in DSB repair, i.e., HR, c-NHEJ, SSA, and MMEJ. Our model recapitulates the well-characterized HR activity observed in wild-type cells in response to DSBs. It also recovers clinically relevant behaviors of BRCA1/FANCS mutants, and their corresponding drug resistance mechanisms ascribed to DNA repair gain-of-function pathogenic variants. Since epigenetic modifiers are dynamic and possible druggable targets, we incorporated them into our model to better characterize their involvement in DSB repair. Our model predicted that loss of the TIP60 complex and its corresponding histone acetylation activity leads to activation of SSA in response to DSBs. Our experimental validation showed that TIP60 effectively prevents activation of RAD52, a key SSA executor, and confirms the suitable use of Boolean network modeling for understanding DNA DSB repair.

In silico analysis of the interaction of de novo peptides derived from Salvia hispanica with anticancer targets.

Cancer is one of the leading causes of death worldwide. Conventional cancer therapies are not selective to cancer cells resulting in serious side effects on patients. Thus, the need for complementary treatments that improve the patient's response to cancer therapy is highly important. To predict and evaluate the physicochemical characteristics and potential anticancer activity of the peptides identified from S. hispanica protein fraction <1 kDa through the use of in silico tools. Peptides derived from Salvia hispanica's protein fraction <1 kDa were identified and analyzed for the prediction of their physicochemical properties. The characterized peptide sequences were then submitted to a multi-criteria decision analysis to identify the peptides that possess the characteristics to potentially exert anticancer activity. Through molecular docking analysis, the potential anticancer activity of the Potentially Anticancer Peptide (PAP)-1, PAP-2, PAP-3, PAP-4, and PAP-5 was estimated by their binding interactions with cancer and apoptosis-related molecules. All five evaluated PAPs exhibited strong binding interactions (< -100 kcal/mol). However, PAP-3 showed the lowest binding free energies with several of the targets. Thus, PAP-3 shows potential to be used as a nutraceutical or ingredient for functional foods that adjuvate in cancer treatment. Conclusions: Through the molecular docking studies, the binding of the PAPs to target molecules of interest for cancer treatment was successfully simulated, from which PAP-3 exhibited the lowest binding free energies. Further in vitro and in vivo studies are required to validate the predictions obtained by the in silico analysis.Communicated by Ramaswamy H. Sarma.

Mapping the Arabidopsis thaliana proteome in PeptideAtlas and the nature of the unobserved (dark) proteome; strategies towards a complete proteome.

This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected PTMs, and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for building the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome - the 'dark' proteome. This dark proteome is highly enriched for certain ( e.g. CLE, CEP, IDA, PSY) but not other ( e.g. THIONIN, CAP,) signaling peptides families, E3 ligases, TFs, and other proteins with unfavorable physicochemical properties. A machine learning model trained on RNA expression data and protein properties predicts the probability for proteins to be detected. The model aids in discovery of proteins with short-half life ( e.g. SIG1,3 and ERF-VII TFs) and completing the proteome. PeptideAtlas is linked to TAIR, JBrowse, PPDB, SUBA, UniProtKB and Plant PTM Viewer.

The Spectrum of Solitary Benign Splenic Lesions-Imaging Clues for a Noninvasive Diagnosis.

Cross-sectional imaging of the upper abdomen, especially if intravenous contrast has been administered, will most likely reveal any acute or chronic disease harbored in the spleen. Unless imaging is performed with the specific purpose of evaluating the spleen or characterizing a known splenic lesion, incidentally discovered splenic lesions pose a small challenge. Solitary benign splenic lesions include cysts, hemangiomas, sclerosing angiomatous nodular transformation (SANT), hamartomas, and abscesses, among others. Sarcoidosis and tuberculosis, although predominantly diffuse micronodular disease processes, may also present as a solitary splenic mass lesion. In addition, infarction and rupture, both traumatic and spontaneous, may take place in the spleen. This review aims to describe the imaging features of the most common benign focal splenic lesions, with emphasis on the imaging findings as these are encountered on routine cross-sectional imaging from a multicenter pool of cases that, coupled with clinical information, can allow a definite diagnosis.

Histopathological Investigation of Varietal Responses to Cercospora beticola Infection Process on Sugar Beet Leaves.

Cercospora leaf spot (CLS) is the most destructive foliar disease in sugar beet (Beta vulgaris). It is caused by Cercospora beticola Sacc., a fungal pathogen that produces toxins and enzymes which affect membrane permeability and cause cell death during infection. In spite of its importance, little is known about the initial stages of leaf infection by C. beticola. Therefore, we investigated the progression of C. beticola on leaf tissues of susceptible and resistant sugar beet varieties at 12-h intervals during the first 5 days after inoculation using confocal microscopy. Inoculated leaf samples were collected and stored in DAB (3,3'-diaminobenzidine) solution until processed. Samples were stained with Alexa Fluor-488-WGA dye to visualize fungal structures. Fungal biomass accumulation, reactive oxygen species (ROS) production, and the area under the disease progress curve were evaluated and compared. ROS production was not detected on any variety before 36 h postinoculation (hpi). C. beticola biomass accumulation, percentage leaf cell death, and disease severity were all significantly greater in the susceptible variety compared with the resistant variety (P < 0.05). Conidia penetrated directly through stomata between 48 to 60 hpi and produced appressoria on stomatal guard cells at 60 to 72 hpi in susceptible and resistant varieties, respectively. Penetration of hyphae inside the parenchymatous tissues varied in accordance with time postinoculation and varietal genotypes. Overall, this study provides a detailed account to date of events leading to CLS disease development in two contrasting varieties.

LncRNA ARGI Contributes to Virus-Induced Pancreatic ß Cell Inflammation Through Transcriptional Activation of IFN-Stimulated Genes.

Type 1 diabetes (T1D) is a complex autoimmune disease that develops in genetically susceptible individuals. Most T1D-associated single nucleotide polymorphisms (SNPs) are located in non-coding regions of the human genome. Interestingly, SNPs in long non-coding RNAs (lncRNAs) may result in the disruption of their secondary structure, affecting their function, and in turn, the expression of potentially pathogenic pathways. In the present work, the function of a virus-induced T1D-associated lncRNA named ARGI (Antiviral Response Gene Inducer) is characterized. Upon a viral insult, ARGI is upregulated in the nuclei of pancreatic ß cells and binds to CTCF to interact with the promoter and enhancer regions of IFNß and interferon-stimulated genes, promoting their transcriptional activation in an allele-specific manner. The presence of the T1D risk allele in ARGI induces a change in its secondary structure. Interestingly, the T1D risk genotype induces hyperactivation of type I IFN response in pancreatic ß cells, an expression signature that is present in the pancreas of T1D patients. These data shed light on the molecular mechanisms by which T1D-related SNPs in lncRNAs influence pathogenesis at the pancreatic ß cell level and opens the door for the development of therapeutic strategies based on lncRNA modulation to delay or avoid pancreatic ß cell inflammation in T1D.

Predicting Optimal Antimalarial Drug Combinations from a Standardized Plasmodium falciparum Humanized Mouse Model.

The development of new combinations of antimalarial drugs is urgently needed to prevent the spread of parasites resistant to drugs in clinical use and contribute to the control and eradication of malaria. In this work, we evaluated a standardized humanized mouse model of erythrocyte asexual stages of Plasmodium falciparum (PfalcHuMouse) for the selection of optimal drug combinations. First, we showed that the replication of P. falciparum was robust and highly reproducible in the PfalcHuMouse model by retrospective analysis of historical data. Second, we compared the relative value of parasite clearance from blood, parasite regrowth after suboptimal treatment (recrudescence), and cure as variables of therapeutic response to measure the contributions of partner drugs to combinations in vivo. To address the comparison, we first formalized and validated the day of recrudescence (DoR) as a new variable and found that there was a log-linear relationship with the number of viable parasites per mouse. Then, using historical data on monotherapy and two small cohorts of PfalcHuMice evaluated with ferroquine plus artefenomel or piperaquine plus artefenomel, we found that only measurements of parasite killing (i.e., cure of mice) as a function of drug exposure in blood allowed direct estimation of the individual drug contribution to efficacy by using multivariate statistical modeling and intuitive graphic displays. Overall, the analysis of parasite killing in the PfalcHuMouse model is a unique and robust experimental in vivo tool to inform the selection of optimal combinations by pharmacometric pharmacokinetic and pharmacodynamic (PK/PD) modeling.

Identifying Barriers and Facilitators for Home Reconstruction for Prevention of Chagas Disease: An Interview Study in Rural Loja Province, Ecuador.

BACKGROUND: Chagas disease (CD) is a tropical parasitic disease spread by triatomine bugs, which are bugs that tend to infest precarious housing in rural and impoverished areas. Reducing exposure to the bugs, and thus the parasite they can carry, is essential to preventing CD in these areas. One promising long-term sustainable solution is to reconstruct precarious houses. Implementing home reconstruction requires an understanding of how householders construct barriers and facilitators they might encounter when considering whether to rebuild their homes. METHODS: To understand barriers and facilitators to home reconstruction, we performed in-depth qualitative interviews with 33 residents of Canton Calvas, Loja, Ecuador, a high-risk endemic region. Thematic analysis was used to identify these barriers and facilitators. RESULTS: The thematic analysis identified three facilitators (project facilitators, social facilitators, and economic facilitators) and two major barriers (low personal economy and extensive deterioration of existing homes). CONCLUSIONS: The study findings provide important loci for assisting community members and for agents of change in home reconstruction projects to prevent CD. Specifically, the project and social facilitators suggest that collective community efforts (minga) are more likely to support home reconstruction intentions than individualist efforts, while the barriers suggest that addressing structural issues of economy and affordability are necessary.

Bullfrogs (Lithobates catesbeianus) as a Potential Source of Foodborne Disease.

In Mexico, bullfrogs (Lithobates catesbeianus) are produced as gourmet food. However, bullfrogs can be carriers of pathogens because the frogs' preferred living conditions occur in stagnant water. The present study aimed to identify bacteria that cause foodborne diseases or are associated with human diseases. For molecular identification, based on the sequential analysis by 16S rRNA or rpoD was conducted on all isolates obtained from bullfrog. A total of 91 bacterial isolates were obtained from bullfrogs; 14 genera and 23 species were identified, including Acinetobacter johnsonii 16.5%; Aeromonas media 14.3%; Aeromonas veronii 13.2%; Providencia rettgeri 7.7%; Citrobacter freundii 6.6%; Aeromonas caviae 4.4%; Aeromonas hydrophila and Elizabethkingia ursingii 3.3%; Pseudomonas stutzeri, Raoultella ornithinolytica, and Shewanella putrefaciens 2.2%; Acinetobacter guillouiae, Acinetobacter pseudolwoffii, Citrobacter portucalensis, Citrobacter werkmanii, Edwardsiella anguillarum, Klebsiella michiganensis, Kluyvera intermedia, Kocuria rosea, Myroides odoratimimus, Myroides odoratus, Proteus sp., and Proteus hauseri 1.1%. In this study, 49.4% of the isolates obtained cause foodborne disease, 19.8% are bacteria that play an important role in the spoilage of food, 5.5% of isolates have nosocomial significance, 13.2% of bacteria are considered to be pollutants of the ecosystem, and in the case of A. salmonicida and Edwardsiella anguillarum (12.1%) to have a negative impact on aquaculture. Acinetobacter pseudolwoffii and Citrobacter portucalensis have not been reported to cause disease. Lastly of these isolates, 97.8% (89/91) can cause disease by food consumption or by direct contact for immunocompromised persons. The presence of these bacteria in bullfrogs represents a significant problem for human health. There is evidence that these microorganisms are pathogenic and frogs may also be reservoirs.

First Report of Leaf Spot of Sugar Beet Caused by Stemphylium vesicarium in Minnesota, USA.

In July 2021, sugar beet (Beta vulgaris L.) leaves with numerous tan to brown spots with white-bleached center and oval to irregularly shaped were collected from a field in Minnesota (MN) (46.2774° N, 96.3100° W), with 15% disease incidence and 30% disease severity. Leaves were washed with tap water then surface disinfected in 1% NaOCl aqueous solution for 1 min. Samples were rinsed thrice with sterile distilled water and dried in a laminar flow hood. A 2-cm leaf disc was plated on potato dextrose agar amended with streptomycin sulfate (200 mg/L) and incubated for four days at 25°C under 12-h light/dark cycle. Single spore cultures were obtained by suspending in sterile water spores harvested from a single colony. The suspension was streaked on a dish with V8 agar media and incubated as described. Five pure cultures were transferred to clarified V8 agar media for morphological feature observations. Colonies were uniform in appearance and developed light to olivaceous green mycelium. Conidia were dark brown to olivaceous green in color and measured 30 × 18 µm (n=20). They were oblong to broadly oval shaped muriform, and multiseptated (1 to 5 septa). Hyphae were septate and pale brown. Conidiophores were short, septate, and light to dark brown in color. Based on the morphological characteristics, isolates were identified as Stemphylium vesicarium (Simmons 1969). Genomic DNA of all five isolates were extracted using the DNeasy Plant Mini Kit (Qiagen, Hilden, Germany). PCR amplification and sequencing of the internal transcribed spacer (ITS) region (ITS1/ITS4 primers), the largest subunit of RNA polymerase II (5F2/7cR primers) (O'Donnell et al. 2009), the plasma membrane ATPase (ATPD-F1/ATPD-R1) gene (Lawrence et al. 2013), glyceraldehyde-3-phosphate-dehydrogenase gene (GAPDH) (gpd1/gpd2) (Berbee et al. 1999), and ß-tubulin gene (Bt2a/Bt2b primers) (Glass and Donaldson 1995) were done using standard procedures. Sequences were submitted to GenBank under accession numbers OP584331 (ITS), OP589289 (RPB2), OP589290 (ATPase), OP994239 (GAPDH) and OP382477 (ß-tubulin). The BLASTN search of the sequences showed 100% similarity with MT629829 (ITS) (525/525 bp), KC584471 (RPB2) (859/859 bp), JQ671770 (ATPase) (794/794 bp), MK105974 (GAPDH) (519/519 bp) and MN410922 (ß-tubulin) (320/320 bp) reference sequences of S. vesicarium. Pathogenicity tests were done using four cv. Maribo MA 504 plants. S. vesicarium spore suspensions (1 × 106/ml) were sprayed on three leaves from each plant. This trial was repeated with three replicates. A similar group of plants were sprayed with autoclaved distilled water to serve as non-inoculated control. All plants were incubated in the mist chamber for 5 days at 25°C, under daily 14/10 light-dark cycles, and >80% relative humidity, then transferred to the greenhouse kept at 23 ± 2°C and a 12-h photoperiod. Fifteen days post-inoculation, all inoculated plants had multiple lesions with dark brown margins with a grayish center, and non-inoculated control plants were asymptomatic. The re-isolated fungus was morphologically similar to isolates retrieved from the field. S. vesicarium was reported on sugar beet in Michigan (Metheny et al. 2022). This is the first report of S. vesicarium causing disease on sugar beet in MN. Stemphylium sp. is a major problem of sugar beet in the Netherlands (Hanse et al. 2015). Efforts should be made to prevent introduction of susceptible beet cultivars so that the disease does not become widespread in the USA.

A long non-coding RNA that harbors a SNP associated with type 2 diabetes regulates the expression of TGM2 gene in pancreatic beta cells.

Introduction: Most of the disease-associated single nucleotide polymorphisms (SNPs) lie in non- coding regions of the human genome. Many of these variants have been predicted to impact the expression and function of long non-coding RNAs (lncRNA), but the contribution of these molecules to the development of complex diseases remains to be clarified. Methods: Here, we performed a genetic association study between a SNP located in a lncRNA known as LncTGM2 and the risk of developing type 2 diabetes (T2D), and analyzed its implication in disease pathogenesis at pancreatic beta cell level. Genetic association study was performed on human samples linking the rs2076380 polymorphism with T2D and glycemic traits. The pancreatic beta cell line EndoC-bH1 was employed for functional studies based on LncTGM2 silencing and overexpression experiments. Human pancreatic islets were used for eQTL analysis. Results: We have identified a genetic association between LncTGM2 and T2D risk. Functional characterization of the LncTGM2 revealed its implication in the transcriptional regulation of TGM2, coding for a transglutaminase. The T2Dassociated risk allele in LncTGM2 disrupts the secondary structure of this lncRNA, affecting its stability and the expression of TGM2 in pancreatic beta cells. Diminished LncTGM2 in human beta cells impairs glucose-stimulated insulin release. Conclusions: These findings provide novel information on the molecular mechanisms by which T2D-associated SNPs in lncRNAs may contribute to disease, paving the way for the development of new therapies based on the modulation of lncRNAs.

Resistance to QoI and DMI Fungicides Does Not Reduce Virulence of C. beticola Isolates in North Central United States.

Cercospora leaf spot (CLS) is a destructive disease limiting sugar beet production and is managed using resistant cultivars, crop rotation, and timely applications of effective fungicides. Since 2016, its causal agent, Cercospora beticola, has been reported to be resistant to quinone outside inhibitors (QoIs) and to have reduced sensitive to demethylation inhibitors (DMIs) in sugar beet growing areas in North Dakota and Minnesota. Isolates of C. beticola resistant to QoIs, DMIs, and both QoIs and DMIs were collected from fields in Foxhome, Minnesota, in 2017. Fitness of these resistant isolates was compared with that of QoI- and DMI-sensitive isolates in laboratory and greenhouse studies. In the lab, mycelial growth, spore production, and spore germination were measured. The results showed that resistant isolates had significantly less mycelial growth and spore production than sensitive isolates, while no significant difference in spore germination was detected. In the greenhouse, six leaf-stage sugar beets were inoculated with a spore suspension made from each resistant group and incubated in separate humidity chambers. CLS disease severity was evaluated visually at 7, 14, and 21 days after inoculation (DAI), and the areas under disease progress curve (AUDPC) were calculated. Resistant isolates had significantly smaller AUDPC but still caused as high disease severity as the sensitive ones at 21 DAI. Although QoI- and/or DMI-resistant isolates had a relatively slower disease development, they still caused high disease severity and need to be factored in disease management practices.

ARAX: a graph-based modular reasoning tool for translational biomedicine.

MOTIVATION: With the rapidly growing volume of knowledge and data in biomedical databases, improved methods for knowledge-graph-based computational reasoning are needed in order to answer translational questions. Previous efforts to solve such challenging computational reasoning problems have contributed tools and approaches, but progress has been hindered by the lack of an expressive analysis workflow language for translational reasoning and by the lack of a reasoning engine-supporting that language-that federates semantically integrated knowledge-bases. RESULTS: We introduce ARAX, a new reasoning system for translational biomedicine that provides a web browser user interface and an application programming interface (API). ARAX enables users to encode translational biomedical questions and to integrate knowledge across sources to answer the user's query and facilitate exploration of results. For ARAX, we developed new approaches to query planning, knowledge-gathering, reasoning and result ranking and dynamically integrate knowledge providers for answering biomedical questions. To illustrate ARAX's application and utility in specific disease contexts, we present several use-case examples. AVAILABILITY AND IMPLEMENTATION: The source code and technical documentation for building the ARAX server-side software and its built-in knowledge database are freely available online (https://github.com/RTXteam/RTX). We provide a hosted ARAX service with a web browser interface at arax.rtx.ai and a web API endpoint at arax.rtx.ai/api/arax/v1.3/ui/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Trans-Proteomic Pipeline: Robust Mass Spectrometry-Based Proteomics Data Analysis Suite.

The Trans-Proteomic Pipeline (TPP) mass spectrometry data analysis suite has been in continual development and refinement since its first tools, PeptideProphet and ProteinProphet, were published 20 years ago. The current release provides a large complement of tools for spectrum processing, spectrum searching, search validation, abundance computation, protein inference, and more. Many of the tools include machine-learning modeling to extract the most information from data sets and build robust statistical models to compute the probabilities that derived information is correct. Here we present the latest information on the many TPP tools, and how TPP can be deployed on various platforms from personal Windows laptops to Linux clusters and expansive cloud computing environments. We describe tutorials on how to use TPP in a variety of ways and describe synergistic projects that leverage TPP. We conclude with plans for continued development of TPP.