Evolutionarily stable gene clusters shed light on the common grounds of pathogenicity in the Acinetobacter calcoaceticus-baumanniicomplex

Nosocomial pathogens of the Acinetobacter calcoaceticus-baumannii (ACB) complex are a cautionary example for the world-wide spread of multi- and pan-drug resistant bacteria. Aiding the urgent demand for novel therapeutic targets, comparative genomics studies between pathogens and their apathogenic relatives shed light on the genetic basis of human-pathogen interaction. Yet, existing studies are limited in taxonomic scope, sensing of the phylogenetic signal, and resolution by largely analyzing genes isolated from their functional contexts. Here, we explored more than 3,000 Acinetobacter genomes in a phylogenomic framework integrating orthology-based phylogenetic profiling and micro-synteny conservation analyses. This allowed to delineate gene clusters in the type strain A. baumannii ATCC 19606 whose evolutionary conservation indicates a functional integration of the subsumed genes. These evolutionarily stable gene clusters (ESGCs) reveal metabolic pathways, transcriptional regulators residing next to their targets but also tie together sub-clusters with distinct functions to form higher-order functional modules. We shortlisted 150 ESGCs that either co-emerged with, or are found preferentially in, the pathogenic ACB clade. They unveil, at an unprecedented resolution, the genetic makeup that coincides with the manifestation of the pathogenic phenotype in the last common ancestor of the ACB clade. Key innovations are the remodeling of the regulatory-effector cascade connecting LuxR/LuxI quorum sensing via an intermediate messenger to biofilm formation, the extension of micronutrient scavenging systems, and the increase of metabolic flexibility by exploiting carbon sources that are provided by the human host. Specifically, we could show that only members of the ACB clade use kynurenine as a sole carbon and energy source, a substance produced by humans to fine-tune the antimicrobial innate immune response. In summary, this study provides a rich and unbiased set of novel testable hypotheses on how pathogenic Acinetobacter interact with and ultimately infect their human host. They disclose promising routes for future therapeutic strategies.

A dual-purpose real-time indicator and transcriptional integrator for calcium detection in living cells

Calcium is a ubiquitous second messenger in eukaryotes, correlated with neuronal activity and T-cell activation among other processes. Real-time calcium indicators such as GCaMP have recently been complemented by newer calcium integrators that convert transient calcium activity into stable gene expression. Here we introduce LuCID, a dual-purpose real-time calcium indicator and transcriptional calcium integrator which combines the benefits of both calcium detection technologies. We show that the calcium-dependent split luciferase component of LuCID provides real-time bioluminescence readout of calcium dynamics in cells, while the GI/FKF1 split GAL4 component of LuCID converts bioluminescence into stable gene expression. We also show that LuCID modular design enables it to also be used for dual-purpose detection of other cellular events such as protein-protein interactions. LuCID should facilitate the study of cell populations and circuits that utilize calcium for signaling.

A robust and stable gene selection algorithm based on graph theory and machine learning

Background Nowadays we are observing an explosion of gene expression data with phenotypes. It enables us to accurately identify genes responsible for certain medical condition as well as classify them for drug target. Like any other phenotype data in medical domain, gene expression data with phenotypes also suffer from being a very underdetermined system. In a very large set of features but a very small sample size domain (e.g. DNA microarray, RNA-seq data, GWAS data, etc.), it is often reported that several contrasting feature subsets may yield near equally optimal results. This phenomenon is known as instability. Considering these facts, we have developed a robust and stable supervised gene selection algorithm to select a set of robust and stable genes having a better prediction ability from the gene expression datasets with phenotypes. Stability and robustness is ensured by class and instance level perturbations, respectively. Results We have performed rigorous experimental evaluations using 10 real gene expression microarray datasets with phenotypes. They reveal that our algorithm outperforms the state-of-the-art algorithms with respect to stability and classification accuracy. We have also performed biological enrichment analysis based on gene ontology-biological processes (GO-BP) terms, disease ontology (DO) terms, and biological pathways. Conclusions It is indisputable from the results of the performance evaluations that our proposed method is indeed an effective and efficient supervised gene selection algorithm.

Reviewing the consequences of genetic purging on the success of rescue programs

Genetic rescue is increasingly considered a promising and underused conservation strategy to reduce inbreeding depression and restore genetic diversity in endangered populations, but the empirical evidence supporting its application is limited to a few generations. Here we discuss on the light of theory the role of inbreeding depression arising from partially recessive deleterious mutations and of genetic purging as main determinants of the medium to long-term success of rescue programs. This role depends on two main predictions: (1) The inbreeding load hidden in populations with a long stable demography increases with the effective population size; and (2) After a population shrinks, purging tends to remove its (partially) recessive deleterious alleles, a process that is slower but more efficient for large populations than for small ones. We also carry out computer simulations to investigate the impact of genetic purging on the medium to long term success of genetic rescue programs. For some scenarios, it is found that hybrid vigor followed by purging will lead to sustained successful rescue. However, there may be specific situations where the recipient population is so small that it cannot purge the inbreeding load introduced by migrants, which would lead to increased fitness inbreeding depression and extinction risk in the medium to long term. In such cases, the risk is expected to be higher if migrants came from a large non-purged population with high inbreeding load, particularly after the accumulation of the stochastic effects ascribed to repeated occasional migration events. Therefore, under the specific deleterious recessive mutation model considered, we conclude that additional caution should be taken in rescue programs. Unless the endangered population harbors some distinctive genetic singularity whose conservation is a main concern, restoration by continuous stable gene flow should be considered, whenever feasible, as it reduces the extinction risk compared to repeated occasional migration and can also allow recolonization events.

Population-level deep sequencing reveals the interplay of clonal and sexual reproduction in the fungal wheat pathogen Zymoseptoria tritici

Pathogens cause significant challenges to global food security. On annual crops, pathogens must re-infect from environmental sources in every growing season. Fungal pathogens have evolved mixed reproductive strategies to cope with the distinct challenges of colonizing growing plants. However, how pathogen diversity evolves during growing seasons remains largely unknown. Here, we performed a deep hierarchical sampling in a single experimental wheat field infected by the major fungal pathogen Zymoseptoria tritici. We analysed whole genome sequences of 177 isolates collected from 12 distinct cultivars replicated in space at three time points of the growing season to maximize capture of genetic diversity. The field population was highly diverse with 37 SNPs per kilobase, a linkage disequilibrium decay within 200–700 bp and a high effective population size. Using experimental infections, we tested a subset of the collected isolates on the dominant cultivar planted in the field. However, we found no significant difference in virulence of isolates collected from the same cultivar compared to isolates collected on other cultivars. About 20 % of the isolate genotypes were grouped into 15 clonal groups. Pairs of clones were disproportionally found at short distances (<5 m), consistent with experimental estimates for per-generation dispersal distances performed in the same field. This confirms predominant leaf-to-leaf transmission during the growing season. Surprisingly, levels of clonality did not increase over time in the field although reproduction is thought to be exclusively asexual during the growing season. Our study shows that the pathogen establishes vast and stable gene pools in single fields. Monitoring short-term evolutionary changes in crop pathogens will inform more durable strategies to contain diseases.

Identification of new reference genes with stable expression patterns for gene expression studies using human cancer and normal cell lines

Reverse transcription—quantitative real-time PCR (RT-qPCR) is a ubiquitously used method in biological research, however, finding appropriate reference genes for normalization is challenging. We aimed to identify genes characterized with low expression variability among human cancer and normal cell lines. For this purpose, we investigated the expression of 12 candidate reference genes in 13 widely used human cancer cell lines (HeLa, MCF-7, A-549, K-562, HL-60(TB), HT-29, MDA-MB-231, HCT 116, U-937, SH-SY5Y, U-251MG, MOLT-4 and RPMI-8226) and, in addition, 7 normal cell lines (HEK293, MRC-5, HUVEC/TERT2, HMEC, HFF-1, HUES 9, XCL-1). In our set of genes, we included SNW1 and CNOT4 as novel candidate reference genes based on the RNA HPA cell line gene data from The Human Protein Atlas. HNRNPL and PCBP1 were also included along with the „classical” reference genes ACTB, GAPDH, IPO8, PPIA, PUM1, RPL30, TBP and UBC. Results were evaluated using GeNorm, NormFiner, BestKeeper and the Comparative ΔCt methods. In conclusion, we propose IPO8, PUM1, HNRNPL, SNW1 and CNOT4 as stable reference genes for comparing gene expression between different cell lines. CNOT4 was also the most stable gene upon serum starvation.

A tale of the monoclonal anti-CD20 antibodies, in tribute to prof. Wacław Szybalski (1921–2020)

Technical advances that lead to the era of targeted therapeutics demanded several milestones that were reached in the second half of the previous century. Professor Wacław Szybalski was the first one to perform a stable gene transfer in eukaryotic cells. To do so, he used his own designed system consisting of HPRT-deficient cells and HAT selective medium. Moreover, the first-ever hybridoma cells were also constructed by Wacław Szybalski’s team. These spectacular achievements made him not only a forerunner of gene therapy, but also became a foundation for immunotherapy, as hybridoma and their selection by the HPRT-HAT system turned into a crucial technical step during production of monoclonal antibodies (mAbs). Herein, we present a story of anti-CD20 mAbs, one of the most successful lines of anticancer drugs. When looking back into history, the prototypic mAb rituximab was considered the biggest step forward in the therapy of B-cell malignancies. Nowadays, the second and third generations of anti-CD20 mAbs are approved in clinical use and numerous breakthrough studies on immune effector mechanisms were conducted with the aforementioned immunotherapeutics as a model.

Reviewing the consequences of genetic purging on the success of rescue programs

Genetic rescue is increasingly considered a promising and underused conservation strategy to reduce inbreeding depression and restore genetic diversity in endangered populations, but the empirical evidence supporting its application is limited to a few generations. Here we discuss on the light of theory the role of inbreeding depression arising from partially recessive deleterious mutations and of genetic purging as main determinants of the medium to long-term success of rescue programs. This role depends on two main predictions: (1) The inbreeding load hidden in populations with a long stable demography increases with the effective population size; and (2) After a population shrinks, purging tends to remove its (partially) recessive deleterious alleles, a process that is slower but more efficient for large populations than for small ones. We also carry out computer simulations to investigate the impact of genetic purging on the medium to long term success of genetic rescue programs. For some scenarios, it is found that hybrid vigor followed by purging will lead to sustained successful rescue. However, there may be specific situations where the recipient population is so small that it cannot purge the inbreeding load introduced by migrants, which would lead to increased fitness inbreeding depression and extinction risk in the medium to long term. In such cases, the risk is expected to be higher if migrants came from a large non-purged population with high inbreeding load, particularly after the accumulation of the stochastic effects ascribed to repeated occasional migration events. Therefore, under the specific deleterious recessive mutation model considered, we conclude that additional caution should be taken in rescue programs. Unless the endangered population harbors some distinctive genetic singularity whose conservation is a main concern, restoration by continuous stable gene flow should be considered, whenever feasible, as it reduces the extinction risk compared to repeated occasional migration and can also allow recolonization events.

Evaluation And Validation of Reliable Reference Genes For Quantitative Real-Time PCR Analysis of The Gene Expression In Macadamia Integrifolia

Background: Macadamia integrifolia, a new economically important crop, the kernel oil is rich in bioactive compound and monounsaturated fatty acid. Gene expression analysis of qRT-PCR is beneficial to understand the complex regulatory networks of macadamia.Results: In this study, the expression stability of 11 traditional housekeeping genes including α-tubulin (TUBa), β–tubulin (TUBb), malate dehydrogenase (MDH), 18S ribosome RNA (18S), glyceraldehyde-3- phosphate dehydrogenase (GAPDH), α-elongation factor 1 (EF1a), β- elongation factor 1 (EF1b), ubiquitin (UBQ), ubiquitin-conjugating enzyme (UBC), cyclophilin (CYP) and actin (ACT) were accessed by qRT-PCR in macadamia seedlings under different experimental conditions and tissues. The expression stability of the 11 reference genes was evaluated by the online tool RefFinder, which include ΔCt, geNorm, NormFinder, BestKeeper four commonly software, and then determinated a comprehensive expression stability ranking by integrating above four ranking results based on the geometric mean. Our results show that ACT was the best stable genes for all samples, cold stress, NaCl sress, PEG stress, ABA treatment, MeJA treatment, stem and leaf tissue samples; EF1b is the most stable gene in GA treatment and heat stress samples; UBC and CYP were respectively ranked top in ethylene treatment and root tissue samples. Finally, the reliability of these results was further validated with a target gene SAD by qRT-PCR. Conclusions: In summary, this study evaluated and validated the suitable reference genes for qRT-PCR under different experiment treatment and tissues, and will be useful for further gene expression studies on the molecular mechanisms in Macadamia.

Durable CRISPR-Based Epigenetic Silencing

Development of CRISPR-based epigenome editing tools is important for the study and engineering of biological behavior. Here, we describe the design of a reporter system for quantifying the ability of CRISPR epigenome editors to produce a stable gene repression. We characterize the dynamics of durable gene silencing and reactivation, as well as the induced epigenetic changes of this system. We report the creation of single-protein CRISPR constructs bearing combinations of three epigenetic editing domains, termed KAL, that can stably repress the gene expression. This system should allow for the development of novel epigenome editing tools which will be useful in a wide array of biological research and engineering applications.