Fungal volatile organic compounds: mechanisms involved in their sensing and dynamic communication with plants.

Microbial volatile organic compounds (MVOCs) are mixtures of gas-phase hydrophobic carbon-based molecules produced by microorganisms such as bacteria and fungi. They can act as airborne signals sensed by plants being crucial players in triggering signaling cascades influencing their secondary metabolism, development, and growth. The role of fungal volatile organic compounds (FVOCs) from beneficial or detrimental species to influence the physiology and priming effect of plants has been well studied. However, the plants mechanisms to discern between FVOCs from friend or foe remains significantly understudied. Under this outlook, we present an overview of the VOCs produced by plant-associate fungal species, with a particular focus on the challenges faced in VOCs research: i) understanding how plants could perceive FVOCs, ii) investigating the differential responses of plants to VOCs from beneficial or detrimental fungal strains, and finally, iii) exploring practical aspects related to the collection of VOCs and their eco-friendly application in agriculture.

Bacillus megaterium HgT21: a Promising Metal Multiresistant Plant Growth-Promoting Bacteria for Soil Biorestoration.

The environmental deterioration produced by heavy metals derived from anthropogenic activities has gradually increased. The worldwide dissemination of toxic metals in crop soils represents a threat for sustainability and biosafety in agriculture and requires strategies for the recovery of metal-polluted crop soils. The biorestoration of metal-polluted soils using technologies that combine plants and microorganisms has gained attention in recent decades due to the beneficial and synergistic effects produced by its biotic interactions. In this context, native and heavy metal-resistant plant growth-promoting bacteria (PGPB) play a crucial role in the development of strategies for sustainable biorestoration of metal-contaminated soils. In this study, we present a genomic analysis and characterization of the rhizospheric bacterium Bacillus megaterium HgT21 isolated from metal-polluted soil from Zacatecas, Mexico. The results reveal that this autochthonous bacterium contains an important set of genes related to a variety of operons associated with mercury, arsenic, copper, cobalt, cadmium, zinc and aluminum resistance. Additionally, halotolerance-, beta-lactam resistance-, phosphate solubilization-, and plant growth-promotion-related genes were identified. The analysis of resistance to metal ions revealed resistance to mercury (HgII+), arsenate [AsO4]³-, cobalt (Co2+), zinc (Zn2+), and copper (Cu2+). Moreover, the ability of the HgT21 strain to produce indole acetic acid (a phytohormone) and promote the growth of Arabidopsis thaliana seedlings in vitro was also demonstrated. The genotype and phenotype of Bacillus megaterium HgT21 reveal its potential to be used as a model of both plant growth-promoting and metal multiresistant bacteria. IMPORTANCE Metal-polluted environments are natural sources of a wide variety of PGPB adapted to cope with toxic metal concentrations. In this work, the bacterial strain Bacillus megaterium HgT21 was isolated from metal-contaminated soil and is proposed as a model for the study of metal multiresistance in spore-forming Gram-positive bacteria due to the presence of a variety of metal resistance-associated genes similar to those encountered in the metal multiresistant Gram-negative Cupriavidus metallidurans CH34. The ability of B. megaterium HgT21 to promote the growth of plants also makes it suitable for the study of plant-bacteria interactions in metal-polluted environments, which is key for the development of techniques for the biorestoration of metal-contaminated soils used for agriculture.

An Upgrade on the Surveillance System of SARS-CoV-2: Deployment of New Methods for Genetic Inspection.

SARS-CoV-2 variants surveillance is a worldwide task that has been approached with techniques such as Next Generation Sequencing (NGS); however, this technology is not widely available in developing countries because of the lack of equipment and limited funding in science. An option is to deploy a RT-qPCR screening test which aids in the analysis of a higher number of samples, in a shorter time and at a lower cost. In this study, variants present in samples positive for SARS-CoV-2 were identified with a RT-qPCR mutation screening kit and were later confirmed by NGS. A sample with an abnormal result was found with the screening test, suggesting the simultaneous presence of two viral populations with different mutations. The DRAGEN Lineage analysis identified the Delta variant, but there was no information about the other three mutations previously detected. When the sequenced data was deeply analyzed, there were reads with differential mutation patterns, that could be identified and classified in terms of relative abundance, whereas only the dominant population was reported by DRAGEN software. Since most of the software developed to analyze SARS-CoV-2 sequences was aimed at obtaining the consensus sequence quickly, the information about viral populations within a sample is scarce. Here, we present a faster and deeper SARS-CoV-2 surveillance method, from RT-qPCR screening to NGS analysis.

Transcriptome Analysis Unveils Gln3 Role in Amino Acids Assimilation and Fluconazole Resistance in Candida glabrata.

After Candida albicans, Candida glabrata is one of the most common fungal species associated with candidemia in nosocomial infections. Rapid acquisition of nutrients from the host is important for the survival of pathogens which possess the metabolic flexibility to assimilate different carbon and nitrogen compounds. In Saccharomyces cerevisiae, nitrogen assimilation is controlled through a mechanism known as Nitrogen Catabolite Repression (NCR). NCR is coordinated by the action of four GATA factors; two positive regulators, Gat1 and Gln3, and two negative regulators, Gzf3 and Dal80. A mechanism in C. glabrata similar to NCR in S. cerevisiae has not been broadly studied. We previously showed that in C. glabrata, Gln3, and not Gat1, has a major role in nitrogen assimilation as opposed to what has been observed in S. cerevisiae in which both factors regulate NCR-sensitive genes. Here, we expand the knowledge about the role of Gln3 from C. glabrata through the transcriptional analysis of BG14 and gln3Δ strains. Approximately, 53.5% of the detected genes were differentially expressed (DEG). From these DEG, amino acid metabolism and ABC transporters were two of the most enriched KEGG categories in our analysis (Up-DEG and Down-DEG, respectively). Furthermore, a positive role of Gln3 in AAA assimilation was described, as was its role in the transcriptional regulation of ARO8. Finally, an unexpected negative role of Gln3 in the gene regulation of ABC transporters CDR1 and CDR2 and its associated transcriptional regulator PDR1 was found. This observation was confirmed by a decreased susceptibility of the gln3Δ strain to fluconazole.

Long-insert clone experimental evidence for assembly improvement and chimeric chromosomes detection in an allopentaploid beer yeast.

Lager beer is made with the hybrid Saccharomyces pastorianus. Many publicly available S. pastorianus genome assemblies are highly fragmented due to the difficulties of assembling hybrid genomes, such as the presence of homeologous chromosomes from both parental types, and translocations between them. To improve the assembly of a previously sequenced lager yeast hybrid Saccharomyces sp. 790 and elucidate its genome structure, we proposed the use of alternative experimental evidence. We determined the phylogenetic position of Saccharomyces sp. 790 and established it as S. pastorianus 790. Then, we obtained from this yeast a bacterial artificial chromosome (BAC) genomic library with its BAC-end sequences (BESs). To analyze these data, we developed a pipeline (applicable to other assemblies) that classifies BES pairs alignments according to their orientation. For the case of S. pastorianus 790, paired-end BESs alignments validated parts of the assembly and unpaired-end ones suggested contig joins or misassemblies. Importantly, the BACs library was preserved and used for verification experiments. Unpaired-end alignments were used to upgrade the previous assembly and provided an improved detection of translocations. With this, we proposed a genome structure of S. pastorianus 790, which was similar to that of other lager yeasts; however, when we estimated chromosome copy number and experimentally measured its genome size, we discovered that one key difference is the outstanding S. pastorianus 790 ploidy level (allopentaploid). Altogether, our results show the value of combining bioinformatic analyses with experimental data such as long-insert clone information to improve a short-read assembly of a hybrid genome.

Chromosome-Level Genome Assembly of the American Cranberry (Vaccinium macrocarpon Ait.) and Its Wild Relative Vaccinium microcarpum.

The American cranberry (Vaccinium macrocarpon Ait.) is an iconic North American fruit crop of great cultural and economic importance. Cranberry can be considered a fruit crop model due to its unique fruit nutrient composition, overlapping generations, recent domestication, both sexual and asexual reproduction modes, and the existence of cross-compatible wild species. Development of cranberry molecular resources started very recently; however, further genetic studies are now being limited by the lack of a high-quality genome assembly. Here, we report the first chromosome-scale genome assembly of cranberry, cultivar Stevens, and a draft genome of its close wild relative species Vaccinium microcarpum. More than 92% of the estimated cranberry genome size (492 Mb) was assembled into 12 chromosomes, which enabled gene model prediction and chromosome-level comparative genomics. Our analysis revealed two polyploidization events, the ancient γ-triplication, and a more recent whole genome duplication shared with other members of the Ericaeae, Theaceae and Actinidiaceae families approximately 61 Mya. Furthermore, comparative genomics within the Vaccinium genus suggested cranberry-V. microcarpum divergence occurred 4.5 Mya, following their divergence from blueberry 10.4 Mya, which agrees with morphological differences between these species and previously identified duplication events. Finally, we identified a cluster of subgroup-6 R2R3 MYB transcription factors within a genomic region spanning a large QTL for anthocyanin variation in cranberry fruit. Phylogenetic analysis suggested these genes likely act as anthocyanin biosynthesis regulators in cranberry. Undoubtedly, these new cranberry genomic resources will facilitate the dissection of the genetic mechanisms governing agronomic traits and further breeding efforts at the molecular level.

How Many Genes Are Expressed in a Transcriptome? Estimation and Results for RNA-Seq.

RNA-seq experiments estimate the number of genes expressed in a transcriptome as well as their relative frequencies. However, an undetermined number of genes can remain undetected due to their low expression relative to the sample size (sequence depth). Estimation of the true number of genes expressed in a transcriptome is essential in order to determine which genes are exclusively expressed in specific tissues or under particular conditions. A reliable estimate of the true number of expressed genes is also required to accurately measure transcriptome changes and to predict the sequencing depth needed to increase the proportion of detected genes. This problem is analogous to ecological sampling problems such as estimating the number of species at a given site. Here we present a non-parametric estimator for the number of undetected genes as well as for the extra sample size needed to detect a given proportion of the undetected genes. Our estimators are superior to ones already published by having smaller standard errors and biases. We applied our method to a set of 32 publicly available RNA-seq experiments, including the evaluation of 311 individually sequenced libraries. We found that in the majority of the cases more than one thousand genes are undetected, and that on average approximately 6% of the expressed genes per accession remain undetected. This figure increases to approximately 10% if individual sequencing libraries are analyzed. Our method is also applicable to metagenomic experiments. Using our method, the number of undetected genes as well as the sample size needed to detect them can be calculated, leading to more accurate and complete gene expression studies.