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Background: Pseudomonas aeruginosa is a major cause of hospital-acquired and chronic infections, characterised by an extraordinary capacity to develop antimicrobial resistance through the selection of chromosomal mutations, leading to treatment failure. Here, we designed and tested a hybridisation-based capture system for the enrichment of genes of interest before sequencing to monitor resistant populations genomics directly from clinical samples., Methods: A panel for enrichment before sequencing of close to 200 genes related to P. aeruginosa antimicrobial resistance, multilocus sequence typing, mutability or virulence was designed, synthesised (KAPA HyperCap, Roche) and initially validated in vitro using a multidrug-resistant ST175 isolate and representative isolates from major P. aeruginosa clades. In vivo testing included ventilator associated pneumonia by MDR P. aeruginosa in ICU (3-10 sequential samples from 3 patients) and chronic respiratory infection by hypermutable P. aeruginosa in cystic fibrosis (8 sequential samples from a single patient covering a 4-year period). Results from direct sequencing with the enrichment panel were compared with those of whole genome sequencing (WGS) and phenotypic profiling of 10 isolated colonies per sample., Findings: In vitro assays confirmed the selectivity of the enrichment panel and the correct identification of the vast mutational resistome of ST175, including specific mutations even when introduced in a 1:100 proportion. In vivo performance was at least equivalent to sequencing 10 colonies per sample, including the accurate identification of the sequence types and the basal and acquired mutational resistome. To note, specific resistance mutations, such as those in ampC leading to resistance to novel β-lactams, could be traced even at frequencies of 1%. Moreover, the coselection of mutator populations and antibiotic resistance mutations, predicted in theoretical and in vitro studies, was evidenced in vivo., Interpretation: This proof-of-concept study demonstrates that resistance genomics of P. aeruginosa can be analysed directly from clinical samples, determining not only a considerable reduction in turnaround time and cost from a diagnostics perspective, but also an unprecedented potency for accurate monitoring of in vivo population dynamics in bacterial infections., Funding: Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación and Unión Europea-NextGenerationEU., Competing Interests: Declaration of interests AO and RC have participated in educational programs organised by MSD, Pfizer and Shionogi and conducted research studies financed by MSD and Shionogi. JPH has participated in educational programs organised by MSD, Pfizer, Menarini and Angelini and in advisory boards organised by Advanz Pharma, Tillots, and GILEAD., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Aiming to increase the reproducibility of biomedical research results, biobanks obtain human tissues of the highest quality and carry out different storage methods adapted to the needs of analytical technique to be performed by the biomedical researchers. However, there is much controversy and little data concerning the real impact of different stabilization methods on tissue quality, integrity and functionality of derived biomolecules. The influence of four stabilization methods [RNAlater (RNL), snap freezing (SF), snap freezing using Optimal Cutting Tissue compound (SF-OCT) and formalin-fixed paraffin-embedded (FFPE)] on RNA quality and integrity was evaluated in paired samples of lung tissue. RNA integrity was evaluated through PCR-endpoint assays amplifying six fragments of different length of the HPRT1 gene and RNA Integrity Number (RIN). To evaluate the difference of tissue functionality among the stabilization methods tested, RT-qPCRs were performed focusing on the differential expression of the HPRT1, SNRPD3 and Jun genes. RNA from the samples preserved with the RNL or SF-OCT method showed better integrity compared to SF and FFPE, measured by PCR-endpoint and RT-qPCR assays. However, only statistically significant differences were observed between the RNA from FFPE and other stabilization methods when gene expression of HPRT1, SNRPD3 and Jun housekeeping genes were determined by RT-qPCR. For the three mentioned genes, Cq and RIN values were highly correlated. The present work describes the fragility of SF samples, being critical the moment just before RNA extraction, although further experiments of tissue RNA are needed. Standardization pre-analytic workflow can lead to improved reproducibility between biomedical research studies. The present study demonstrated clear evidences about the impact of the stabilization method on RNA derived from lung human tissue samples.

Background: Optimal contribution methods have proved to be very efficient for controlling the rates at which coancestry and inbreeding increase and therefore, for maintaining genetic diversity. These methods have usually relied on pedigree information for estimating genetic relationships between animals. However, with the large amount of genomic information now available such as high-density single nucleotide polymorphism (SNP) chips that contain thousands of SNPs, it becomes possible to calculate more accurate estimates of relationships and to target specific regions in the genome where there is a particular interest in maximising genetic diversity. The objective of this study was to investigate the effectiveness of using genomic coancestry matrices for: (1) minimising the loss of genetic variability at specific genomic regions while restricting the overall loss in the rest of the genome; or (2) maximising the overall genetic diversity while restricting the loss of diversity at specific genomic regions., Results: Our study shows that the use of genomic coancestry was very successful at minimising the loss of diversity and outperformed the use of pedigree-based coancestry (genetic diversity even increased in some scenarios). The results also show that genomic information allows a targeted optimisation to maintain diversity at specific genomic regions, whether they are linked or not. The level of variability maintained increased when the targeted regions were closely linked. However, such targeted management leads to an important loss of diversity in the rest of the genome and, thus, it is necessary to take further actions to constrain this loss. Optimal contribution methods also proved to be effective at restricting the loss of diversity in the rest of the genome, although the resulting rate of coancestry was higher than the constraint imposed., Conclusions: The use of genomic matrices when optimising contributions permits the control of genetic diversity and inbreeding at specific regions of the genome through the minimisation of partial genomic coancestry matrices. The formula used to predict coancestry in the next generation produces biased results and therefore it is necessary to refine the theory of genetic contributions when genomic matrices are used to optimise contributions.

Background: The most efficient method to maintain genetic diversity in populations under conservation programmes is to optimize, for each potential parent, the number of offspring left to the next generation by minimizing the global coancestry. Coancestry is usually calculated from genealogical data but molecular markers can be used to replace genealogical coancestry with molecular coancestry. Recent studies showed that optimizing contributions based on coancestry calculated from a large number of SNP markers can maintain higher levels of diversity than optimizing contributions based on genealogical data. In this study, we investigated how SNP density and effective population size impact the use of molecular coancestry to maintain diversity., Results: At low SNP densities, the genetic diversity maintained using genealogical coancestry for optimization was higher than that maintained using molecular coancestry. The performance of molecular coancestry improved with increasing marker density, and, for the scenarios evaluated, it was as efficient as genealogical coancestry if SNP density reached at least 3 times the effective population size.However, increasing SNP density resulted in reduced returns in terms of maintained diversity. While a benefit of 12% was achieved when marker density increased from 10 to 100 SNP/Morgan, the benefit was only 2% when it increased from 100 to 500 SNP/Morgan., Conclusions: The marker density of most SNP chips already available for farm animals is sufficient for molecular coancestry to outperform genealogical coancestry in conservation programmes aimed at maintaining genetic diversity. For the purpose of effectively maintaining genetic diversity, a marker density of around 500 SNPs/Morgan can be considered as the most cost effective density when developing SNP chips for new species. Since the costs to develop SNP chips are decreasing, chips with 500 SNPs/Morgan should become available in a short-term horizon for non domestic species.