Biology subjects

Carazzolle, M. F.

Publications and source records attributed to Carazzolle, M. F..

10 recordsLinked to original sources

bioRxiv2026

DYNAMICS OF CONTAMINANT MICROBES IN BIOETHANOL PRODUCTION FROM SUGARCANE

The dynamics and impact of microbial contaminants in industrial sugarcane bioethanol production in Brazil were investigated through a two-year metagenomic study across two biorefineries. Shotgun metagenomic sequencing revealed that temporal shifts in the contaminant microbiome dynamics within production seasons were more pronounced than inter-annual or inter-mill variations. While Saccharomyces spp. dominated, bacterial communities, primarily within the Firmicutes phylum and dominated by the genera Lactobacillus, Limosilactobacillus, and Bacillus, exhibited dynamic changes. Correlation analyses with industrial process parameters revealed a complex interplay: lower Lactobacillus levels in one mill were associated with increased ethanol yield, whereas higher levels in another mill correlated with reduced yeast viability and increased flocculation. The presence of Limosilactobacillus was linked to decreased yeast viability, whereas Bacillus showed potential for inhibiting both Lactobacillus and Limosilactobacillus. These findings highlight the nuanced and species-specific impacts of bacterial contaminants on bioethanol production, underscoring the need for strain-level functional studies and targeted interventions to optimize fermentation efficiency and stability in industrial settings.

microbiology↗

bioRxiv2025

Abnormal expression of splicing regulators RBFOX and NOVA is associated with aberrant splicing patterns at the Neurexin-3 gene in a monogenic autism spectrum disorder

Autism spectrum disorders are diseases characterized by a combination of cognitive, behavioral and neurological symptoms. A complex interplay between environmental factors and a multitude of genetic determinants, most of them composed of low-risk variants, impose difficulties in understanding the molecular and cellular underpinnings of these conditions. In some cases, autistic patients have been shown to display alterations in splicing patterns of several genes, but the extent to which this phenomenon is common in the context of these multifactorial disorders is unknown, nor is it known if monogenic cases of autism also display dysregulation of splicing. Moreover, very few studies have investigated the causal links between splicing alterations in specific genes and the phenotypic characteristics of the neural tissue in autism patients. In this study, we have focused on a monogenic type of autism caused by haploinsufficiency of the Transcription Factor 4 gene, known as Pitt-Hopkins Syndrome. We show that neurons and organoids derived from patients with this disease have altered expression of splicing regulators in the NOVA and RBFOX families, accompanied by aberrant splicing patterns in a substantial number of genes involved in neural tissue development and synapse organization. We focused on a gene encoding a member of the Neurexin Family, the splicing of which normally leads to the production of transcript variants coding for both transmembrane and secreted protein isoforms. In Pitt-Hopkins Syndrome neurons, we detected an aberrant splicing pattern that results in lower expression of the secreted isoform and its corresponding transcript, a phenomenon that may explain why the neural tissue in these patients have decreased electrical activity through impaired synapse organization. Our data shed light on the role splicing regulation plays in a monogenic type of autism.

neuroscience↗

bioRxiv2025

Epistatic mutations in ISC metabolism synergize with cell cycle regulation and the PPP to enhance xylose fermentation and acetic acid tolerance in industrial yeast

Efficient utilization of complex biomass-derived sugars and tolerance to inhibitors are key requirements for the viability of lignocellulosic-based biorefineries. In this study, a two-stage evolution of an industrial yeast strain engineered with a xylose isomerase pathway yielded strain AceY.14, which exhibited improved fermentative performance and increased tolerance to acetic acid. Whole-genome sequencing of the evolved strain identified SNPs in ZWF1, a component of the pentose phosphate pathway (PPP), and in the G1 cyclin gene CLN3, both of which were functionally validated through CRISPR and reverse engineering. The zwf1E191D mutation reduced xylitol accumulation, alleviating inhibition of xylose isomerase and enhancing flux through the non-oxidative branch of the PPP, while the frameshift cln3T556fsmutation unexpectedly improved acetic acid tolerance and xylose consumption in the evolved strain, also affecting cell size and growth. Genome sequencing of AceY.14 also revealed a significant reduction in the xylA gene copy number, likely decreasing the metabolic burden associated with high xylose isomerase expression. A synergistic effect was observed in the isu1{Delta}/zwf1{Delta} double mutant, further boosting xylose consumption rates. A diploid derivative (AceY-2n) demonstrated high productivity and robustness in fermentations using hydrolysates from various lignocellulosic feedstocks, highlighting the strains potential for industrial-scale applications. These findings reveal novel metabolic targets for strain optimization and offer valuable insights for the rational engineering of yeast platforms for sustainable biofuel and bioproduct production.

synthetic biology↗

bioRxiv2025

A Transcriptomic Atlas of Macauba Palm Reveals Organ-Specific Gene Expression and Stress-Related Pathways

The macauba palm (Acrocomia aculeata) is an emerging oilseed species with promising applications in biodiesel production, as well as in food and cosmetic industries. Native to the Neotropical, it is incipiently domesticated and distributed across diverse environments and edaphoclimatic conditions. However, genomic studies of macauba are limited due to the scarcity of publicly available sequence data, as it is considered a non-model plant. In this study, we present an exploratory analysis of a transcriptome dataset comprising seven organs (roots, bulbs, male and female flowers, leaves, leaf sheath, and fruits). A total of 22,703 transcripts were assembled into a single reference dataset. Of these, 9,729 transcripts (42.85%) were annotated using KEGG orthology. Gene expression profiling revealed 306, 32, 41, 159, 158 and 916 organ-specific transcripts in leaves, leaf sheaves, bulbs, flowers, fruit and root, respectively. Comparative analysis with African oil palm (Elaeis guineensis) and date palm (Phoenix dactylifera) revealed 55 gene families exclusive to macauba palm. In addition, 221 transcripts related to drought stress were identified, grouped into 112 families. Root libraries revealed 7,091 fungal transcripts - approximately 3.9% of all reads - mainly derived from arbuscular mycorrhizal fungi (AMF) Rhizophagus spp. These findings highlight the central role of signal transduction pathways in response to environmental stresses in macauba palm. The transcriptome dataset generated in this study provides a valuable genomic resource for future genotype-phenotype investigations in macauba palm. Furthermore, the presence of AMF-associated transcripts suggests a potentially important role for these symbiotic fungi in macauba palm growth and development.

plant biology↗

bioRxiv2024

Unveiling genetic anchors in Saccharomyces cerevisiae: QTL mapping identifies IRA2 as a key player in ethanol tolerance and beyond

Ethanol stress in Saccharomyces cerevisiae is a well-studied phenomenon, but pinpointing specific genes or polymorphisms governing ethanol tolerance remains a subject of ongoing debate. Naturally found in sugar-rich environments, this yeast has evolved to withstand high ethanol concentrations, primarily produced during fermentation in the presence of suitable oxygen or sugar levels. Originally a defense mechanism against competing microorganisms, yeast-produced ethanol is now a cornerstone of brewing and bioethanol industries, where customized yeasts require high ethanol resistance for economic viability. However, yeast strains exhibit varying degrees of ethanol tolerance, ranging from 8% to 20%, making the genetic architecture of this trait complex and challenging to decipher. In this study, we introduce a novel QTL mapping pipeline to investigate the genetic markers underlying ethanol tolerance in an industrial bioethanol S. cerevisiae strain. By calculating missense mutation frequency in a prominent QTL region within a population of 1011 S. cerevisiae strains, we uncovered rare occurrences in gene IRA2. Following molecular validation, we confirmed the significant contribution of this gene to ethanol tolerance, particularly in concentrations exceeding 12% of ethanol. IRA2 pivotal role in stress tolerance due to its participation in the Ras-cAMP pathway was further supported by its involvement in other tolerance responses, including thermotolerance, low pH tolerance, and resistance to acetic acid. Understanding the genetic basis of ethanol stress in S. cerevisiae holds promise for developing robust yeast strains tailored for industrial applications.

genetics↗

bioRxiv2021

Genetic mapping of a bioethanol yeast strain reveals new targets for aldehyde- and thermotolerance

Current technology that enables bioethanol production from agricultural biomass imposes harsh conditions for Saccharomyces cerevisiaes metabolism. In this work, the genetic architecture of industrial bioethanol yeast strain SA-1 was evaluated. SA-1 segregant FMY097 was previously described as highly aldehyde resistant and here also as thermotolerant: two important traits for the second-generation industry. A Quantitative Trait Loci (QTL) mapping of 5-hydroxymethylfurfural (HMF) -resistant segregants of hybrid FMY097/BY4742 disclosed a region in chromosome II bearing alleles with uncommon non-synonymous (NS) single nucleotide polymorphisms (SNPs) in FMY097: MIX23, PKC1, SEA4, and SRO77. Allele swap to susceptible laboratory strain BY4742 revealed that SEA4FMY097 enhances robustness towards HMF, but the industrial fitness could not be fully recovered. The genetic network arising from the causative genes in the QTL window suggests that intracellular signaling TOR (Target of Rapamycin) and CWI (Cell Wall Integrity) pathways are regulators of this phenotype in FMY097. Because the QTL mapping did not result in one major allelic contribution to the evaluated trait, a background effect in FMY097s HMF resistance is expected. Quantification of NADPH - cofactor implied in endogenous aldehyde detoxification reactions - supports the former hypothesis, given its high availability in FMY097. Regarding thermotolerance, SEA4FMY097 grants BY4742 ability to grow in temperatures as high as 38 {degrees}C in liquid, while allele PKC1FMY097 allows growth up to 40 {degrees}C in solid medium. Both SEA4FMY097 and PKC1FMY097 encode rare NS SNPs, not found in other >1,013 S. cerevisiae. Altogether, these findings point towards crucial membrane and stress mediators for yeast robustness. KEY POINTSO_LIQTL mapping of the HMF-resistant strain FMY097 reveals a region enriched with SNPs in Chr II C_LIO_LISEA4FMY097 has rare non-synonymous mutations and improves cell growth at 10 mM HMF and 38{degrees}C C_LIO_LIPKC1FMY097 has rare non-synonymous mutations and improves cell growth at 40 {degrees}C in solid media C_LI

genetics↗

bioRxiv2021

Plant-associated microbiomes promote nutrient turnover in impoverished substrates of a biodiversity hotspot

The substrates of the Brazilian campos rupestres have extremely low concentrations of key nutrients, mainly phosphorus, imposing severe restrictions to plant growth. Regardless, this ecosystem harbors enormous biodiversity which raises the question of how nutrients are cycled and acquired by the biosphere. To uncover the nutrient turnover potential of plant-associated microorganisms in the campos rupestres, we investigated the compositions and functions of microbiomes associated with two species of the Velloziaceae family that grow over distinct substrates (soil and rock). Amplicon, metagenomic, and metagenome-assembled genome sequence data showed that the campos rupestres harbor a novel assemblage of plant-associated prokaryotes and fungi. Compositional analysis revealed that the plant-associated soil and rock communities differed in taxonomic structure but shared a core of highly efficient colonizers that were strongly coupled with nutrient mobilization. Investigation of functional and abundance data revealed that the plant hosts actively recruit communities by exuding organic compounds and that the root-associated microbiomes possess a diverse repertoire of phosphorus turnover mechanisms. We also showed that the microbiomes of both plant species encompass novel populations capable of mobilizing nitrogen and that the substrate strongly influences the dynamics of this cycle. Our results show that the interplay between plants and their microbiomes shapes nutrient turnover in the campos rupestres. We highlight that investigation of microbial diversity is fundamental to understand plant fitness in stressful environments.

genomics↗

bioRxiv2021

Adaptive evolution of Moniliophthora PR-1 proteins towards its pathogenic lifestyle

Moniliophthora perniciosa and Moniliophthora roreri are hemibiotrophic fungi that harbor a large number of Pathogenesis-Related 1 genes, many of which are induced in the biotrophic interaction with Theobroma cacao. Here, we provide evidence that the evolution of PR-1 in Moniliophthora was adaptive and potentially related to the emergence of the parasitic lifestyle in this genus. Phylogenetic analysis revealed conserved PR-1 genes, shared by many Agaricales saprotrophic species, that have diversified in new PR-1 genes putatively related to pathogenicity in Moniliophthora, as well as in recent specialization cases within both species. PR-1 families in Moniliophthora with higher evolutionary rates exhibit induced expression in the biotrophic interaction and positive selection clues, supporting the hypothesis that these proteins accumulated adaptive changes in response to host-pathogen arm race. Furthermore, we show that the highly diversified MpPR-1 genes are not induced by two phytoalexins, suggesting detoxification might not be their main function as proposed before.

evolutionary biology↗

bioRxiv2020

Transcriptome analysis of three Agave fiber-producing cultivars suitable for biochemicals and biofuels production in semiarid regions

O_LIAgaves, which have been grown commercially for fiber or alcoholic beverages, are emerging as a candidate crop for biochemicals and biofuels production in semiarid regions because of their high productivity in low rainfall areas, drought tolerance, and low lignin content. C_LIO_LIIn this work, we present the transcriptomic atlas of Agave sisalana, Agave fourcroydes, and agave hybrid 11648 (A. amaniensis x A. angustifolia) under prolonged drought in field conditions. Leaf, stem, and root tissues were sequenced, and gene expression profiles were correlated with biomass composition, enzymatic hydrolysis of cell wall carbohydrates, histochemical analysis, and non-structural carbohydrates content. C_LIO_LIDifferences in biomass accessibility were attributed to either lignin content or lignin composition, possibly through modification of s/g ratio promoted by changes in Caffeic Acid 3-O-Methyltransferase (COMT) transcript abundance. Unlike most plants, the most highly expressed transcripts do not encode photosynthetic proteins, but rather involved in stress response. Although the three cultivars presented quantitative differences in global gene expression, they activated a highly overlapping set of genes. The main molecular strategies employed by agave to cope with high-temperature and drought seem to consist in overexpressing HSP and LEA, as well as promoting raffinose accumulation as an osmolyte. C_LIO_LIIn conclusion, our data provide vital new genetic information for the study of Agave species and provide new insights into cell wall architecture, recalcitrance, and resistance to abiotic stresses for these species. C_LI

plant biology↗

bioRxiv2019

RNAsamba: coding potential assessment using ORF and whole transcript sequence information

MotivationThe advent of high-throughput sequencing technologies made it possible to obtain large volumes of genetic information, quickly and inexpensively. Thus, many efforts are devoted to unveil the biological roles of genomic elements, being one of the main tasks the identification of protein-coding and long non-coding RNAs.\n\nResultsWe describe RNAsamba, a tool to predict the coding potential of RNA molecules from sequence information using a deep-learning model that processes both the whole sequence and the ORF to look for patterns that distinguish coding and non-coding RNAs. We evaluated the model in the classification of coding and non-coding transcripts of humans and five other model organisms and show that RNAsamba mostly outperforms other state-of-the-art methods. We also show that RNAsamba can identify coding signals in partial-length ORFs and UTR sequences, evidencing that its model is not dependent on the presence of complete coding regions. RNAsamba is a fast and easy tool that can provide valuable contributions to genome annotation pipelines.\n\nAvailability and implementationThe source code of RNAsamba is freely available at:https://github.com/apcamargo/RNAsamba.

bioinformatics↗