Selection of endogenous genes for gene expression studies in Eucalyptus under biotic (Puccinia psidii) and abiotic (acibenzolar-S-methyl) stresses using RT-qPCR

<p>Abstract</p> <p>Background</p> <p>Rust caused by <it>Puccinia psidii </it>Winter has been limiting for the establishment of new <it>Eucalyptus </it>plantations, as well as for resprouting of susceptible genetic materials. Identifying host genes involved in defense responses is important to elucidate resistance mechanisms. Reverse transcription-quantitative PCR is the most common method of mRNA quantitation for gene expression analysis. This method generally employs a reference gene as an internal control to normalize results. A good endogenous control transcript shows minimal variation due to experimental conditions.</p> <p>Findings</p> <p>We analyzed the expression of 13 genes to identify transcripts with minimal variation in leaves of 60-day-old clonal seedlings of two <it>Eucalyptus </it>clones (rust-resistant and susceptible) subjected to biotic (<it>P. psidii</it>) and abiotic (acibenzolar-S-methyl, ASM) stresses.</p> <p>Conclusions</p> <p>For tissue samples of clones that did not receive any stimulus, a combination of the <it>eEF2 </it>and <it>EglDH </it>genes was the best control for normalization. When pathogen-inoculated and uninoculated plant samples were compared, <it>eEF2 </it>and <it>UBQ </it>together were more appropriate as normalizers. In ASM-treated and untreated leaves of both clones, transcripts of the <it>CYP </it>and <it>elF4B </it>genes combined were the ones with minimal variation. Finally, when comparing expression in both clones for ASM-treated leaves, <it>P. psidii</it>-inoculated leaves, ASM-treated plus <it>P. psidii</it>-inoculated leaves, and their respective controls, the genes with the most stable expression were <it>EgIDH </it>and <it>UBQ</it>. The chitinase gene, which is highly expressed in studies on plant resistance to phytopathogens, was used to confirm variation in gene expression due to the treatments.</p

New genes of Xanthomonas citri subsp. citri involved in pathogenesis and adaptation revealed by a transposon-based mutant library

<p>Abstract</p> <p>Background</p> <p>Citrus canker is a disease caused by the phytopathogens <it>Xanthomonas citri </it>subsp. <it>citri</it>, <it>Xanthomonas fuscans </it>subsp. <it>aurantifolli </it>and <it>Xanthomonas alfalfae </it>subsp. <it>citrumelonis</it>. The first of the three species, which causes citrus bacterial canker type A, is the most widely spread and severe, attacking all citrus species. In Brazil, this species is the most important, being found in practically all areas where citrus canker has been detected. Like most phytobacterioses, there is no efficient way to control citrus canker. Considering the importance of the disease worldwide, investigation is needed to accurately detect which genes are related to the pathogen-host adaptation process and which are associated with pathogenesis.</p> <p>Results</p> <p>Through transposon insertion mutagenesis, 10,000 mutants of <it>Xanthomonas citri </it>subsp. <it>citri </it>strain 306 (Xcc) were obtained, and 3,300 were inoculated in Rangpur lime (<it>Citrus limonia</it>) leaves. Their ability to cause citrus canker was analyzed every 3 days until 21 days after inoculation; a set of 44 mutants showed altered virulence, with 8 presenting a complete loss of causing citrus canker symptoms. Sequencing of the insertion site in all 44 mutants revealed that 35 different ORFs were hit, since some ORFs were hit in more than one mutant, with mutants for the same ORF presenting the same phenotype. An analysis of these ORFs showed that some encoded genes were previously known as related to pathogenicity in phytobacteria and, more interestingly, revealed new genes never implicated with <it>Xanthomonas </it>pathogenicity before, including hypothetical ORFs. Among the 8 mutants with no canker symptoms are the <it>hrpB4 </it>and <it>hrpX </it>genes, two genes that belong to type III secretion system (TTSS), two hypothetical ORFS and, surprisingly, the <it>htrA </it>gene, a gene reported as involved with the virulence process in animal-pathogenic bacteria but not described as involved in phytobacteria virulence. Nucleic acid hybridization using labeled cDNA probes showed that some of the mutated genes are differentially expressed when the bacterium is grown in citrus leaves. Finally, comparative genomic analysis revealed that 5 mutated ORFs are in new putative pathogenicity islands.</p> <p>Conclusion</p> <p>The identification of these new genes related with Xcc infection and virulence is a great step towards the understanding of plant-pathogen interactions and could allow the development of strategies to control citrus canker.</p

Proteome of the phytopathogen Xanthomonas citri subsp. citri: a global expression profile

<p>Abstract</p> <p>Background</p> <p>Citrus canker is a disease caused by <it>Xantomonas citri </it>subsp.<it>citri (Xac)</it>, and has emerged as one of the major threats to the worldwide citrus crop because it affects all commercial citrus varieties, decreases the production and quality of the fruits and can spread rapidly in citrus growing areas. In this work, the first proteome of <it>Xac </it>was analyzed using two methodologies, two-dimensional liquid chromatography (2D LC) and tandem mass spectrometry (MS/MS).</p> <p>Results</p> <p>In order to gain insight into the metabolism of <it>Xac</it>, cells were grown on two different media (<b>NB </b>- Nutrient Broth and <b>TSE </b>- Tryptone Sucrose broth enriched with glutamic acid), and proteins were proteolyzed with trypsin and examined by 2D LC-MS/MS. Approximately 39% of all predicted proteins by annotation of <it>Xac </it>were identified with their component peptides unambiguously assigned to tandem mass spectra. The proteins, about 1,100, were distributed in all annotated functional categories.</p> <p>Conclusions</p> <p>This is the first proteomic reference map for the most aggressive strain of <it>Xanthomonas </it>pathogen of all orange varieties. The compilation of metabolic pathways involved with bacterial growth showed that <it>Xac </it>expresses a complete central and intermediary metabolism, replication, transcription and translation machineries and regulation factors, distinct membrane transporters (ABC, MFS and pumps) and receptors (MCP, TonB dependent and metabolites acquisition), two-component systems (sensor and regulatory components) and response regulators. These data corroborate the growth curve <it>in vitro </it>and are the first reports indicating that many of these genome annotated genes are translated into operative in <it>Xac</it>. This proteomic analysis also provided information regarding the influence of culture medium on growth and protein expression of <it>Xac</it>.</p

Reweighting simulated events using machine-learning techniques in the CMS experiment

Data Availability Statement: The manuscript has no associated data CERN for the benefit of the CMS Collaboration. [Author’s comment: Release and preservation of data used by the CMS Collaboration as the basis for publications is guided by the CMS data preservation, re-use and open access policy.]Code Availability Statement: The manuscript has associated code/software in a data repository. [Author’s comment: The CMS core software is publicly available on GitHub (https://github.com/cms-sw/cmssw) policy (https://doi.org/10.7483/OPENDATA.CMS.1BNU.8V1W)].Data analyses in particle physics rely on an accurate simulation of particle collisions and a detailed simulation of detector effects to extract physics knowledge from the recorded data. Event generators together with a geant-based simulation of the detectors are used to produce large samples of simulated events for analysis by the LHC experiments. These simulations come at a high computational cost, where the detector simulation and reconstruction algorithms have the largest CPU demands. This article describes how machine-learning (ML) techniques are used to reweight simulated samples obtained with a given set of parameters to samples with different parameters or samples obtained from entirely different simulation programs. The ML reweighting method avoids the need for simulating the detector response multiple times by incorporating the relevant information in a single sample through event weights. Results are presented for reweighting to model variations and higher-order calculations in simulated top quark pair production at the LHC. This ML-based reweighting is an important element of the future computing model of the CMS experiment and will facilitate precision measurements at the High-Luminosity LHC.Funded by SCOAP3

Energy-scaling behavior of intrinsic transverse-momentum parameters in Drell-Yan simulation

Data Availability: Release and preservation of data used by the CMS Collaboration as the basis for publications is guided by the CMS data preservation, re-use, and open access policy https://dx.doi.org/10.7483/OPENDATA.CMS.7347.JDWH .A preprint version of the article is available on arXiv, arXiv:2409.17770v2 [hep-ph] (https://arxiv.org/abs/2409.17770). [v2] Tue, 8 Apr 2025 23:23:48 UTC (450 KB). Comments: Replaced with the published version. Added the journal reference and the DOI. All the figures and tables can be found at https://cms-results.web.cern.ch/cms-results/public-results/publications/GEN-22-001 (CMS Public Pages). Subjects: High Energy Physics - Phenomenology (hep-ph); High Energy Physics - Experiment (hep-ex). Report numbers: CMS-GEN-22-001, CERN-EP-2024-216An analysis is presented based on models of the intrinsic transverse momentum (intrinsic ) of partons in nucleons by studying the dilepton transverse momentum in Drell-Yan events. Using parameter tuning in event generators and existing data from fixed-target experiments and from hadron colliders, our investigation spans 3 orders of magnitude in center-of-mass energy and 2 orders of magnitude in dilepton invariant mass. The results show an energy-scaling behavior of the intrinsic parameters, independent of the dilepton invariant mass at a given center-of-mass energy.We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid and other centers for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC, the CMS detector, and the supporting computing infrastructure provided by the following funding agencies: SC (Armenia), BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES and BNSF (Bulgaria); CERN; CAS, MoST, and NSFC (China); MINCIENCIAS (Colombia); MSES and CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); ERC PRG, RVTT3 and MoER TK202 (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); SRNSF (Georgia); BMBF, DFG, and HGF (Germany); GSRI (Greece); NKFIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LMTLT (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MES and NSC (Poland); FCT (Portugal); MESTD (Serbia); MCIN/AEI and PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); MHESI and NSTDA (Thailand); TUBITAK and TENMAK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (USA)

The CMS Statistical Analysis and Combination Tool: Combine

Metrics: https://link.springer.com/article/10.1007/s41781-024-00121-4/metricsThis paper describes the Combine software package used for statistical analyses by the CMS Collaboration. The package, originally designed to perform searches for a Higgs boson and the combined analysis of those searches, has evolved to become the statistical analysis tool presently used in the majority of measurements and searches performed by the CMS Collaboration. It is not specific to the CMS experiment, and this paper is intended to serve as a reference for users outside of the CMS Collaboration, providing an outline of the most salient features and capabilities. Readers are provided with the possibility to run Combine and reproduce examples provided in this paper using a publicly available container image. Since the package is constantly evolving to meet the demands of ever-increasing data sets and analysis sophistication, this paper cannot cover all details of Combine. However, the online documentation referenced within this paper provides an up-to-date and complete user guide.CERN (European Organization for Nuclear Research)STFC (United Kingdom)Marie-Curie programme and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 101115353, 101002207, and COST Action CA16108 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundatio