Teresa Rito

Genetic literacy increasingly shapes decisions in healthcare, research participation, and everyday life. As direct-to-consumer genetic testing expands and genomic data become more accessible, the n...

Molecular clocks use the accumulation of genetic changes to estimate the timing of evolutionary and demographic events. Since their formulation in the 1960s, molecular clocks have evolved from relatively simple strict-rate assumptions into a diverse set of statistical frameworks that include strict, relaxed, local and time-dependent models. In this review, we examine the conceptual basis of molecular-clock inference and the biological, demographic and methodological factors that influence clock estimates. We distinguish mutation rates from substitution rates and discuss how molecular, genomic, life-history, environmental and population-level processes can affect estimated evolutionary rates. We then review the main analytical approaches used to estimate branch lengths and divergence times, including maximum likelihood, Bayesian inference, parsimony-based methods and regression-based techniques; we also focus on the statistical evaluation of clock-like behaviour. Particular attention is given to calibration, as molecular clocks only become informative for absolute time estimation when genetic distances are anchored to an external temporal framework. We review calibration strategies based on fossils, geological and biogeographic events, founder events, ancient sequences, pedigrees, direct mutation-rate estimates, longitudinal sampling, secondary calibrations and externally estimated substitution rates. Finally, we discuss cases in which molecular-clock estimates show concordance or discordance with independent archaeological, palaeontological or epidemiological evidence, as well as cases where apparent agreement may reflect circular reasoning. We argue that molecular clocks remain essential tools for evolutionary biology, but that their reliability depends on explicit model testing, transparent calibration choices and careful interpretation of the results.

Klebsiella pneumoniae (Kp) is a leading cause of hospital-acquired infections representing a growing threat driven by emerging multidrug resistance (MDR) and hypervirulence. In this study, we aim to characterise the genomic and epidemiological landscape of Kp in a Portuguese regional hospital (Braga) lacking prior genomic data. We performed whole-genome sequencing of 115 Kp isolates collected from colonisation and infection cases. Phylogenetic, resistance, and virulence profiles were integrated with clinical and epidemiological data. Genomic analysis revealed high diversity, with 83.5% of isolates forming evolutionary clusters. Several novel sequence types (STs), as ST2623 and ST1562, were detected for the first time in Portugal to our knowledge. ST45, uncommonly associated with carbapenem resistance, emerged as dominant with multiple blaKPC-3-positive isolates. Results suggest active transmission of carbapenem resistance genes. One hypervirulent carbapenem-resistant ST13 warrants careful surveillance. Virulence-associated yersiniabactin was common (66.9%) but other hypervirulence loci were rare. Epidemiologically, MDR-Kp was associated with older hospitalised patients with prior antibiotic use and invasive procedures, while community-acquired infections were genetically diverse and affected younger patients with comorbidities. An unusually low number of respiratory infections was observed, likely reflecting strict COVID-19 mitigation measures. Although widespread dissemination of hypervirulent or MDR clones was not evident, the emergence of high-risk lineages and the detection of ongoing gene transmission episodes underscore the need for ongoing genomic surveillance. Immediate mitigation strategies could include reducing device use and hospital transfers, given the high prevalence of colonisation.

The timing of the settlement of Sahul—the Pleistocene landmass formed by present-day New Guinea, Australia, and Tasmania that existed until ~9000 years ago (~9 ka)—remains highly contentious. The so-called “long chronology” posits the first main arrivals at ~60 to 65 ka, whereas a “short chronology” proposes 47 to 51 ka. Here, we exhaustively analyze an unprecedentedly large mitogenome dataset ( n = 2456) encompassing the full range of diversity from the indigenous populations of Australia, New Guinea, and Oceania, including a lineage related to those of New Guinea in an archaeological sample from Wallacea. We assess these lineages in the context of variation from Southeast Asia and a reevaluation of the mitogenome mutation rate, alongside genome-wide and Y-chromosome variation, and archaeological and climatological evidence. In contrast to recent recombinational dating approaches, we find support for the long chronology, suggesting settlement by ~60 ka via at least two distinct routes into Sahul.

Human mitochondrial DNA (mtDNA) is a relevant marker in evolutionary and population genetics, including ancient DNA (aDNA) research, due to inherent characteristics. However, aDNA is prone to damage and sequencing artefacts, potentially confounding evolutionary interpretations. To assess evolutionary patterns in ancient and modern mtDNA, we built a phylogeny comprising 63,965 modern and 3757 ancient public mitogenomes, classified mutations by genomic region and functional effect, and analysed distribution, frequency, and predicted pathogenicity of private and pre-terminal mutations, investigating purifying selection. We compared mutation class ratios (non-synonymous, rRNA, tRNA, nonsense vs. synonymous) across ancient and modern terminal branches and pre-terminal nodes. The predicted pathogenicity of non-synonymous mutations was evaluated across major European haplogroups using three tools. Ancient variants exhibited higher ratios of potentially deleterious mutations and significantly elevated pathogenicity scores compared to modern and pre-terminal branches, highlighting a mutation load likely inflated by damage-related artefacts. Remarkably, nonsense mutations—largely incompatible with life—were over 70 times more frequent in aDNA. The correlation between mutation ratios and predicted deleteriousness across haplogroups suggests a pattern incompatible with biological persistence or relaxed selection alone. These findings highlight the importance of rigorous quality control for ancient data in evolutionary inference, molecular clock calibration, and pathogenic variant identification.

Tuberculosis (TB) remains a major cause of global mortality and is a significant public health challenge, including in specific Portuguese regions. Key aspects in understanding TB’s historical dynamics and impacts on past and present populations are to consider cultural changes and the implementation of public health policies through time. Therefore, this survey aims to provide a more accurate history of TB in Portugal, based on the analysis of sanitary measures through time, illustrating the role of TB in the evolution of public health in Portugal. For this, bibliographic research was conducted across various academic databases and major Portuguese libraries, statistical archives, and public health repositories. Therefore, a detailed chronology, along with some new statistical data, is presented and correlated with sanitary and public health measures, illustrating the role of TB in the evolution of the public health system in Portugal. This research enhances our understanding of the past and sheds light on ongoing TB challenges.

The renewable, abundant , and low-cost nature of lignocellulosic biomass can play an important role in the sustainable production of bioenergy and several added-value bioproducts, thus providing alternative solutions to counteract the global energetic and industrial demands. The efficient conversion of lignocellulosic biomass greatly relies on the catalytic activity of carbohydrate-active enzymes (CAZymes). Finding novel and robust biocatalysts, capable of being active under harsh industrial conditions, is thus imperative to achieve an economically feasible process. In this study, thermophilic compost samples from three Portuguese companies were collected, and their metagenomic DNA was extracted and sequenced through shotgun sequencing. A novel multi-step bioinformatic pipeline was developed to find CAZymes and characterize the taxonomic and functional profiles of the microbial communities, using both reads and metagenome-assembled genomes (MAGs) as input. The samples’ microbiome was dominated by bacteria, where the classes Gammaproteobacteria, Alphaproteobacteria, and Balneolia stood out for their higher abundance, indicating that the degradation of compost biomass is mainly driven by bacterial enzymatic activity. Furthermore, the functional studies revealed that our samples are a rich reservoir of glycoside hydrolases (GH), particularly of GH5 and GH9 cellulases, and GH3 oligosaccharide-degrading enzymes. We further constructed metagenomic fosmid libraries with the compost DNA and demonstrated that a great number of clones exhibited β-glucosidase activity. The comparison of our samples with others from the literature showed that, independently of the composition and process conditions, composting is an excellent source of lignocellulose-degrading enzymes. To the best of our knowledge, this is the first comparative study on the CAZyme abundance and taxonomic/functional profiles of Portuguese compost samples. Key points: • Sequence- and function-based metagenomics were used to find CAZymes in compost samples. • Thermophilic composts proved to be rich in bacterial GH3, GH5, and GH9 enzymes. • Compost-derived fosmid libraries are enriched in clones with β-glucosidase activity.

Following the emergence of COVID-19 in December 2019, caused by the coronavirus SARS-CoV-2, the disease spread dramatically worldwide. The use of genomics to trace the dissemination of the virus and the identification of novel variants was essential in defining measures for containing the disease. We aim to evaluate the global effort to genomically characterize the circulating lineages of SARS-CoV-2, considering the data deposited in GISAID, the major platform for data sharing in a massive worldwide collaborative undertaking. We contextualize data for nearly three years (January 2020–October 2022) for the major contributing countries, percentage of characterized isolates and time for data processing in the context of the global pandemic. Within this collaborative effort, we also evaluated the early detection of seven major SARS-CoV-2 lineages, G, GR, GH, GK, GV, GRY and GRA. While Europe and the USA, following an initial period, showed positive results across time in terms of cases sequenced and time for data deposition, this effort is heterogeneous worldwide. Given the current immunization the major threat is the appearance of variants that evade the acquired immunity. In that scenario, the monitoring of those hypothetical variants will still play an essential role.