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campestris pv. incanae (Xci). Xci is the causal agent of black rot of garden stock and closely related to Xcc. PCR using pncB_fw1 and Xcr_rv1, or pncB_2 and Xcr_rv2, amplified DNA fragments only in Xcr. Multiplex PCR analysis easily distinguished Xcc and Xcr from bacterial colonies isolated on growth media and detected the pathogen in symptomatic leaves. Multiplex nested PCR detected the contamination of one seed with Xcc and/or Xcr infection from 1000 seeds. Therefore, the PCR primers designed in this study therefore helped detect and discriminate between Xcc and Xcr. KEY POINTS • Xanthomonas campestris pv. campestris (Xcc) and pv. raphani (Xcr) were investigated. • Novel primers were designed following whole-genome comparison analyses. [https://www.selleckchem.com/products/azd6738.html AZD6738 cell line] • Multiplex PCR with new primers distinguished Xcc and Xcr simultaneously.The aim of this study is to select a cisplatin-resistant Saccharomyces cerevisiae strain to look for new molecular markers of resistance and the identification of mechanisms/interactions involved. A resistant strain was obtained after 80 days of cisplatin exposure. Then, total protein extraction, purification, and identification were carried out, in wild-type (wt) and resistant strains, by tandem mass spectrometry using a "nano HPLC-ESI-MS/MS" ion trap system. The increase in the exponentially modified protein abundance index (emPAI) (resistant vs wt strains) was calculated to study the increase in protein expression. "Genemania" software ( http//www.Genemania.org/ ) was used to compare the effects, functions, and protein interactions. KEGG tool was used for metabolic pathway analysis. Data are available via ProteomeXchange with identifier PXD020665. The cisplatin-resistant strain showed 2.5 times more resistance than the wt strain for the inhibitory dose 50% (ID50) value (224 μg/ml vs 89.68 μg/ml) and 2.78 times more resistant for the inhibitory dose 90% (ID90) value (735.2 μg/ml vs 264.04 μg/ml). Multiple deregulated proteins were found in the glutathione and carbon metabolism, oxidative phosphorylation, proteasome, glycolysis and gluconeogenesis, glyoxylate metabolism, fatty acid degradation pathway, citric acid cycle, and ribosome. The most overexpressed proteins in the cisplatin-resistant strain were related to growth and metabolism (QCR2, QCR1, ALDH4, ATPB, ATPA, ATPG, and PCKA), cell structure (SCW10), and thermal shock (HSP26). The results suggest that these proteins could be involved in cisplatin resistance. The resistance acquisition process is complex and involves the activation of multiple mechanisms that interact together. KEY POINTS • Identification of new proteins/genes related to cisplatin resistance • Increased expression of QCR2/QCR1/ALDH4/ATPB/ATPA/SCW10/HSP26/ATPG and PCKA proteins • Multiple molecular mechanisms that interact together are involved in resistance.Several microorganisms are currently being used as production platform for glycolipid biosurfactants, providing a greener alternative to chemical biosurfactants. One of the reasons why these processes are commercially competitive is the fact that microbial producers can efficiently export their product to the extracellular environment, reaching high product titers. Glycolipid biosynthetic genes are often found in a dedicated cluster, amidst which genes encoding a dedicated transporter committed to shuttle the glycolipid to the extracellular environment are often found, as is the case for many other secondary metabolites. Knowing this, one can rely on gene clustering features to screen for novel putative transporters, as described and performed in this review. The above strategy proves to be very powerful to identify glycolipid transporters in fungi but is less valid for bacterial systems. Indeed, the genetics of these export systems are currently largely unknown, but some hints are given. Apart from the direct export of the glycolipid, several other transport systems have an indirect effect on glycolipid production. Specific importers dictate which hydrophilic and hydrophobic substrates can be used for production and influence the final yields. In eukaryotes, cellular compartmentalization allows the assembly of glycolipid building blocks in a highly specialized and efficient way. Yet, this requires controlled transport across intracellular membranes. Next to the direct export of glycolipids, the current state of the art regarding this indirect involvement of transporter systems in microbial glycolipid synthesis is summarized in this review. KEY POINTS • Transporters are directly and indirectly involved in microbial glycolipid synthesis. • Yeast glycolipid transporters are found in their biosynthetic gene cluster. • Hydrophilic and hydrophobic substrate uptake influence microbial glycolipid synthesis.Emerging evidence suggests that Helicobacter pylori infection is associated with metabolic disorders, although the underlying mechanisms are poorly defined. This study aimed to investigate the interaction among H. pylori, a high-fat diet (HFD), and the gut microbiota with glucose regulation and alterations in microbial metabolites. Mice were randomly allocated to H. pylori-infected and noninfected groups fed a chow diet or an HFD. After 4 weeks, two of the HFD groups were given antibiotic cocktails for 8 weeks to eliminate the gut microbiota. The results showed that an HFD significantly promoted increases in body weight, insulin resistance, and glucose intolerance, which were alleviated to normal after antibiotic treatment. H. pylori infection aggravated HFD-induced hyperglycemia, which could not be restored by antibiotics. The perturbation of the gut microbiota was greater in the mice cotreated with H. pylori and an HFD (HFDHp) compared to those administered either H. pylori or an HFD alone, with a loss of diversity, higher abundance of Helicobacter, and lower abundance of Lactobacillus. Furthermore, compared to that of the HFD alone group, the gut microbiota of the HFDHp group was much more susceptible to antibiotic destruction, with extremely lower diversity and dominance of Klebsiella. Fecal metabolome analyses demonstrated that the combination of H. pylori infection and an HFD altered metabolic composition and function, which were linked to glucose dysregulation. H. pylori infection may exacerbate the dysbiosis of the gut microenvironment induced by an HFD, including alterations in the microbiota and metabolites, which weakens the restorative effect of antibiotics and results in the persistence of glucose disorders. KEY POINTS • The interplay of Hp, HFD, and antibiotics on glucose metabolism was firstly explored. • Hp infection impaired the effect of antibiotics on HFD-induced glucose dysregulation. • Hp infection altered gut microbiota and metabolites which aggravated by HFD.