Biology subjects

Jacobus, A. P.

Publications and source records attributed to Jacobus, A. P..

7 recordsLinked to original sources

bioRxiv2026

EasyCAPS: A web tool for restriction-based genotyping and rational CRISPR-Cas9 donor design

Tracking Single Nucleotide Polymorphisms (SNPs) following CRISPR-Cas9 genome editing is a critical yet often labor-intensive step in modern genetic research. Although Sanger sequencing is the conventional method for definitive confirmation, it typically requires substantial time to generate results. In contrast, PCR-based restriction methods like CAPS (Cleaved Amplified Polymorphic Sequence) and dCAPS (derived CAPS) offer rapid and cost-effective alternatives. However, existing dCAPS primer design tools suffer from significant limitations and were largely developed for tracking polymorphisms in plant genomes. Concurrently, CRISPR-Cas9 gene editing requires strategies to prevent the re-cleavage of the edited allele, typically involving the modification of the Protospacer Adjacent Motif (PAM). To address these challenges, we developed EasyCAPS, a web-based tool that integrates dCAPS primer design with advanced functionalities for CRISPR experiments. EasyCAPS overcomes the shortcomings of previous software by enabling restriction enzyme pre-selection and optimizing designs for complex DNA sequences. Its key innovation is the "Hiding PAM" feature, which designs synonymous mutations to mask the Cas9 recognition site while accounting for codon usage bias, thereby facilitating one-step allelic exchange. The utility of the tool was demonstrated through practical applications targeting the HTA1, PHO84, and CAT5 genes, significantly accelerating both genotyping and gene editing processes. We conclude that EasyCAPS is an accessible solution that effectively streamlines molecular biology workflows.

genetics↗

bioRxiv2025

QTL mapping, breeding, and debugging Saccharomyces cerevisiae strains through Reiterated Mass Selection and backcrosSing (ReMaSSing)

BackgroundProducing second-generation ethanol from lignocellulosic hydrolysates (LCHs) poses significant challenges for Saccharomyces cerevisiae due to the presence of fermentation inhibitors. Quantitative trait loci (QTL) mapping of stress-tolerant S. cerevisiae strains is important for identifying adaptive alleles that can enhance yeast fermentation of LCHs. However, the QTL mapping process is labor-intensive, requiring the screening of numerous recombinants and repeated crossings to improve mapping resolution. ResultsWe developed Reiterated Mass Selection and backcrosSing (ReMaSSing) to facilitate the identification of adaptive alleles through QTL mapping and to enhance LCH tolerance in yeast strains. ReMaSSing was applied to populations obtained by crossing the stress-resistant yeast PE-2_H4 with the laboratory strain S288C. Using alternative protocols, we selected haploid or diploid populations with dominant markers, enriching millions of segregants carrying adaptive alleles by propagating them in standard or LCH-supplemented media. The enriched pools were then bulk backcrossed with S288C, and germination of millions of spores generated new recombinant populations for subsequent selection cycles. After five rounds of ReMaSSing, whole-genome sequencing and QTL mapping identified key alleles associated with LCH tolerance, linked to VPS70, CAT5, GCY1, UBP2, MKT1/SAL1, HAP1, and PHO84, which influence growth and mitochondrial function in S288C. Mutations in IRA1 and HTA1, unique to our S288C strain, were also mapped, highlighting ReMaSSings ability to detect and correct deleterious alleles ("bugs"). Allele swapping and competition assays confirmed that the identified QTL improved LCH tolerance and growth, with strains combining adaptive alleles performing over 20% better than the parental S288C. Finally, applying ReMaSSing to breed an LCH-tolerant yeast with a xylose-consuming strain produced recombinants with improved fermentation of xylose-enriched LCH. ConclusionReMaSSing offers a practical protocol for generating QTL mapping populations to identify adaptive alleles in tolerant strains and correct genetic defects in inferior ones. Notably, recombinant populations and clones derived from ReMaSSing outperformed both parental strains in LCH tolerance and growth. Furthermore, we applied ReMaSSing to breed strains with enhanced LCH tolerance, efficient xylose catabolism, and robust ethanol production. Together, these results demonstrate that ReMaSSing is a powerful tool for engineering industrial yeast strains that integrate desirable traits from multiple parental backgrounds.

genomics↗

bioRxiv2024

Engineering Adaptive Alleles for Escherichia coli Growth on Sucrose Using the EasyGuide CRISPR System

Adaptive Laboratory Evolution (ALE) is a powerful approach for mining genetic data to engineer industrial microorganisms. This evolution-informed design requires robust genetic tools to incorporate the discovered alleles into target strains. Here, we introduce the EasyGuide CRISPR, a five-plasmid platform that exploits E. colis natural recombination system to assemble gRNA plasmids from overlapping PCR fragments. The production of gRNAs and donor DNA is further facilitated by using recombination cassettes generated through PCR with 40 to 60-mer oligos. With the new CRISPR toolkit, we constructed 22 gene edits in E. coli DH5, most of which corresponded to alleles mapped in E. coli DH5 and E2348/69 ALE populations selected for sucrose propagation. For DH5 ALE, sucrose consumption was supported by the cscBKA operon expression from a high-copy plasmid. During ALE, plasmid integration into the chromosome, or its copy number reduction due to the pcnB deletion, conferred a 30-35% fitness gain, as demonstrated by CRISPR-engineered strains. A [~]5% advantage was also associated with a [~]40.4 kb deletion involving fli operons for flagella assembly. In E2348/69 ALE, inactivation of the hfl system suggested selection pressures for maintaining {lambda}-prophage dormancy (lysogeny). We further enhanced our CRISPR toolkit using yeast for in vivo assembly of donors and expression cassettes, enabling the establishment of polyhydroxybutyrate synthesis from sucrose. Overall, our study highlights the importance of combining ALE with streamlined CRISPR-mediated allele editing to advance microbial production using cost-effective carbon sources.

genetics↗

bioRxiv2024

Simultaneous enumeration of yeast and bacterial cells in the context of industrial bioprocesses

In scenarios where yeast and bacterial cells coexist, e.g. the food and bioethanol industries, it would be of interest to simultaneously quantify the concentrations of both cell types, since traditional methods used to determine these concentrations individually take more time and resources. Here, we compared different methods for quantifying the fuel ethanol Saccharomyces cerevisiae PE-2 yeast strain and cells from the probiotic Lactiplantibacillus plantarum strain in microbial suspensions. Individual suspensions were prepared ([~]107, yeast cells/mL or [~]109, bacterial cells/mL) and mixed in 1:1 or 100:1 yeast-to-bacteria ratios, covering the range typically encountered in sugarcane biorefineries. The following methods were used: bright field microscopy, manual and automatic Spread-plate and Drop-plate counting, flow cytometry (at 1:1 and 100:1 ratios), and a Coulter counter (at 1:1 and 100:1 ratios). By subjecting the same mixed cell suspension to each technique, we observed that for yeast cell counts in the mixture (1:1 and 100:1 ratios), flow cytometry, the Coulter counter, and both Spread-plate options (manual and automatic CFU counting) yielded statistically similar results, while the Drop-plate and microscopy-based methods gave statistically different results. For bacterial cell quantification, the microscopy-based method, Drop-plate, and both Spread-plate plating options and flow cytometry (1:1 ratio) produced no significantly different results (P>0.05). In contrast, the Coulter counter (1:1 ratio) and flow cytometry (100:1 ratio) presented results statistically different (P<0.05). Additionally, quantifying bacterial cells in a mixed suspension at a 100:1 ratio wasnt possible due to an observed overlap between yeast cell debris and bacterial cells. The results from this work indicate that each method has limitations, advantages, and disadvantages, meaning that the best option will always depend on the application. We present a comparison of the techniques, in terms of time-to-results, cost of analysis and equipment, range of detectable cell/particle diameters, adequacy for simultaneous enumeration, and general pros and cons. Graphical AbstractThis study compares methods for simultaneously quantifying yeast and bacterial cells in a mixed sample, highlighting that in different cell proportions, some methods cannot quantify both cell types and present distinct advantages and limitations regarding time, cost, and precision. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/600471v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@875599org.highwire.dtl.DTLVardef@104b849org.highwire.dtl.DTLVardef@ded39borg.highwire.dtl.DTLVardef@11692b2_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

Optimal trade-off between boosted tolerance and growth fitness during adaptive evolution of yeast to ethanol shocks

The design of selection protocols to obtain bioethanol yeasts with higher alcohol tolerance poses the challenge of improving industrial strains that are already robust to high ethanol levels. Furthermore, yeasts subjected to mutagenesis and selection, or laboratory evolution, often present adaptation trade-offs wherein higher stress tolerance is attained at the expense of growth and fermentation performance. We conducted an adaptive laboratory evolution by challenging four populations (P1-P4) of the Brazilian bioethanol yeast, Saccharomyces cerevisiae PE-2_H4, through 68-82 cycles of 2-h ethanol shocks (19%-30% v/v) and outgrowths. Colonies isolated from the final populations (P1c-P4c) were subjected to whole-genome sequencing, revealing mutations in genes enriched for the cAMP/PKA and trehalose degradation pathways. Fitness analyses of the isolated clones P1c-P3c and reverse-engineered strains demonstrated that mutations were primarily selected for cell viability under ethanol stress, at the cost of decreased growth rates in cultures with or without ethanol. Under this selection regime for stress survival, the population P4 evolved a protective snowflake phenotype resulting from BUD3 disruption. Despite marked adaptation trade-offs, the combination of reverse-engineered mutations cyr1A1474T/usv1{Delta} conferred 5.46% higher fitness than the parental PE-2_H4 for propagation in 8% (v/v) ethanol, with only a 1.07% fitness cost in a culture medium without alcohol. The cyr1A1474T/usv1{Delta} strain and evolved P1c displayed robust fermentations of sugarcane molasses using cell recycling and sulfuric acid treatments, mimicking Brazilian bioethanol production. These results demonstrate that some alleles selected for acute stress survival may further confer stress tolerance and optimal performance under industrial conditions.

evolutionary biology↗

bioRxiv2022

EasyGuide plasmids support in vivo assembly of gRNAs for CRISPR/Cas9 applications in Saccharomyces cerevisiae

Most CRISPR/Cas9 applications in yeast rely on a plasmid-based expression of Cas9 and its guide RNA (gRNA) containing a 20-nucleotides (nts) spacer tailored to each genomic target. The lengthy assembly of this customized gRNA requires at least 3-5 days for its pre-cloning in Escherichia coli, purification, validation, and co-transformation with Cas9 into a yeast strain. Here, we constructed a series of 12 EasyGuide plasmids to simplify CRISPR/Cas9 applications in Saccharomyces cerevisiae. The new vectors provide templates for generating PCR fragments that can assemble up to six functional gRNAs directly into yeasts via homologous recombination between the 20-nts spacers. By dispensing pre-cloning in E. coli, yeast in vivo gRNA assembly significantly reduces the CRISPR/Cas9 experimental workload. A highly efficient yeast genome editing procedure, involving PCR amplification of gRNAs and donors, followed by their transformation into a Cas9-expressing strain, can be easily accomplished in a single day.

synthetic biology↗

bioRxiv2020

Comparative genomics supports that Brazilian bioethanol Saccharomyces cerevisiae comprise a unified group of domesticated strains related to cachaca spirit yeasts

Ethanol production from sugarcane is a key renewable fuel industry in Brazil. Major drivers of this alcoholic fermentation are Saccharomyces cerevisiae strains that originally were contaminants to the system and yet prevail in the industrial process. Here we present newly sequenced genomes (using Illumina short-read and PacBio long-read data) of two monosporic isolates (H3 and H4) of the S. cerevisiae PE-2, a predominant bioethanol strain in Brazil. The assembled genomes of H3 and H4, together with 42 draft genomes of sugarcane-fermenting (fuel ethanol plus cachaca) strains, were compared against those of the reference S288c and diverse S. cerevisiae. All genomes of bioethanol yeasts have amplified SNO2(3)/SNZ2(3) gene clusters for vitamin B1/B6 biosynthesis, and display ubiquitous presence of SAM-dependent methyl transferases, a gene family rare in S. cerevisiae. Widespread amplifications of quinone oxidoreductases YCR102C/YLR460C/YNL134C, and the structural or punctual variations among aquaporins and components of the iron homeostasis system, likely represent adaptations to industrial fermentation. Interesting is the pervasive presence among the bioethanol/cachaca strains of a five-gene cluster (Region B) that is a known phylogenetic signature of European wine yeasts. Combining genomes of H3, H4, and 195 yeast strains, we comprehensively assessed whole-genome phylogeny of these taxa using an alignment-free approach. The 197-genome phylogeny substantiates that bioethanol yeasts are monophyletic and closely related to the cachaca and wine strains. Our results support the hypothesis that biofuel-producing yeasts in Brazil may have been co-opted from a pool of yeasts that were pre-adapted to alcoholic fermentation of sugarcane for the distillation of cachaca spirit, which historically is a much older industry than the large-scale fuel ethanol production.

genomics↗