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Hamede, R.

Publications and source records attributed to Hamede, R..

10 recordsLinked to original sources

Response to "No evidence that transmissible cancer has shifted from emergence to endemism in Tasmanian devils"

Herein, we rebut the critique of Patton et al. (2020), entitled, "No evidence that a transmissible cancer has shifted from emergence to endemism", by Stammnitz et al. (2024). First and foremost, the authors do not conduct any phylogenetic or epidemiological analyses to rebut the inferences from the main results of the Patton et al. (2020) article, rendering the title of their rebuttal without evidence or merit. Additionally, Stammnitz et al. (2024) present a phylogenetic tree based on only 32 copy number variants (not typically used in phylogenetic analyses and evolve in a completely different way than DNA sequences) to "rebut" our tree that was inferred from 436.1 kb of sequence data and nearly two orders of magnitude more parsimony-informative sites (2520 SNPs). As such it is not surprising that their phylogeny did not have a similar branching pattern to ours, given that support for each branch of their tree was weak and the essentially formed a polytomy. That is, one could rotate their resulting tree in any direction and by nature, it would not match ours. While the authors are correct that we used suboptimal filtering of our raw whole genome sequencing data, re-analyses of the data with 30X coverage, as suggested, resulted in a mutation rate similar to that reported in Stammnitz et al. (2024). Most importantly, when we re-analyzed our data, as well as Stammnitz et al.s own data, the results of the Patton et al. (2020) article are supported with both datasets. That is, the effective transmission rate of DFTD has transitioned over time to approach one, suggesting endemism; and, the spread of DFTD is rapid and omnidirectional despite the observed east-to-west wave of spread. Overall, Stammnitz et al. (2024) not only fail to provide evidence to contradict the findings of Patton et al. (2020), but rather help support the results with their own data.

evolutionary biology↗

Fast and Furious: Metabolic Pathways Fuelling Devil Facial Tumour Disease

Devil Facial Tumour Diseases (DFTD), threatening Tasmanian devils, consist of two distinct transmissible cancers, DFT1 and DFT2, with differing origins and geographic spread. We investigated the metabolic differences between DFT1 and DFT2, examining cell viability, metabolic outputs, and bulk gene expression. Using both DFT1 and DFT2 cell lines and biopsies, we found that glycolysis, oxidative phosphorylation, glutamate metabolism and fatty acid synthesis are all essential for the survival of both tumour types. However, DFT2 exhibited higher rates of glycolysis and lactate generation compared to DFT1. This coincided with elevated ATP production, cholesterol biosynthesis and ROS generation, as well as an increased reliance on fatty acid metabolism. Furthermore, DFT2 is less metabolically adaptable than DFT1, being unable to switch to oxidative phosphorylation as DFT1 can when required. These metabolic changes in DFT2, in conjunction with its higher growth rate, suggests a more aggressive cancer phenotype than DFT1. Our findings highlight distinct metabolic adaptations in DFT2 that may contribute to its competitive advantage.

cancer biology↗

Effects of a transmissible cancer on life-history traits in Tasmanian devils

Shifts in life history traits, such as timing of reproduction, can help mediate population declines following perturbations, and early reproduction should be favoured when adult survival is impacted more than juvenile survival. In Tasmanian devils, following the emergence of a fatal transmissible cancer, females started to breed precocially (i.e., at age one instead of typically age two) and the same time as populations started to decline following disease emergence. Here, we focus on a diseased site (Freycinet Peninsula, Tasmania, Australia) with 18 years of continuous mark-recapture data to test: (1) whether rates of precocial breeding in females continued to increase after the initial rise after the emergence of the disease, (2) whether there was a relationship between body size and breeding success for either one-year-olds or adult females (i.e., at least two-years-old), and (3) whether there was inbreeding depression in breeding success for either age category. We show that rates of precocial breeding did not continue to rise, and that the proportion of precocially breeding females has plateaued at around 50%. We also show that there was no effect of body size on the probability of breeding for either one-year-old or for adult females. Finally, we show that there was no evidence for inbreeding depression in breeding success for either age class. We discuss possible constraints that may have inhibited further rise in rates of precocial breeding in the context of limitations to growth in the offspring of precocially breeding (and therefore smaller) females.

evolutionary biology↗

The spectral underpinnings of pathogen spread on animal networks

Predicting what factors promote or protect populations from infectious disease is a fundamental epidemiological challenge. Social networks, where nodes represent hosts and edges represent direct or indirect contacts between them, are important in quantifying these aspects of infectious disease dynamics. However, how network structure and epidemic parameters interact in empirical networks to promote or protect animal populations from infectious disease remains a challenge. Here we draw on advances in spectral graph theory and machine learning to build predictive models of pathogen spread on a large collection of empirical networks from across the animal kingdom. We show that the spectral features of an animal network are powerful predictors of pathogen spread for a variety of hosts and pathogens and can be a valuable proxy for the vulnerability of animal networks to pathogen spread. We validate our findings using interpretable machine learning techniques and provide a flexible web application for animal health practitioners to assess the vulnerability of a particular network to pathogen spread.

ecology↗

The evolution of two transmissible cancers in Tasmanian devils

Tasmanian devils have spawned two transmissible cancer lineages, named devil facial tumour 1 (DFT1) and devil facial tumour 2 (DFT2). We investigated the genetic diversity and evolution of these clones by analysing 78 DFT1 and 41 DFT2 genomes relative to a newly assembled chromosome-level reference. Time-resolved phylogenetic trees reveal that DFT1 first emerged in 1986 (1982-1989), and DFT2 in 2011 (2009-2012). Subclone analysis documents transmission of heterogeneous cell populations. DFT2 has faster mutation rates than DFT1 across all variant classes, including substitutions, indels, rearrangements, transposable element insertions and copy number alterations, and we identify a hypermutated DFT1 lineage with defective DNA mismatch repair. Several loci show plausible evidence of positive selection in DFT1 or DFT2, including loss of chromosome Y and inactivation of MGA, but none are common to both cancers. This study illuminates the parallel long-term evolution of two transmissible cancers inhabiting a common niche in Tasmanian devils.

cancer biology↗

Cathelicidin-3 associated with serum extracellular vesicles enables early diagnosis of a transmissible cancer

The identification of practical early diagnosis biomarkers is a cornerstone of improved prevention and treatment of cancers. Such a case is devil facial tumour disease (DFTD), a highly lethal transmissible cancer afflicting virtually an entire species, the Tasmanian devil (Sarcophilus harrisii). Despite a latent period that can exceed one year, to date DFTD diagnosis requires visual identification of tumour lesions. To enable earlier diagnosis, which is essential for the implementation of effective conservation strategies, we analysed the extracellular vesicle (EV) proteome of 87 Tasmanian devil serum samples. The antimicrobial peptide cathelicidin-3 (CATH3) was enriched in serum EVs of both devils with clinical DFTD (87.9% sensitivity and 94.1% specificity) and devils with latent infection (i.e., collected while overtly healthy, but 3-6 months before subsequent DFTD diagnosis; 93.8% sensitivity and 94.1% specificity). As antimicrobial peptides can play a variety of roles in the cancer process, our results suggest that the specific elevation of serum EV-associated CATH3 may be mechanistically involved in DFTD pathogenesis. This EV-based approach to biomarker discovery is directly applicable to improving understanding and diagnosis of a broad range of diseases in other species, and these findings directly enhance the capacity of conservation strategies to ensure the viability of the imperilled Tasmanian devil population.

cancer biology↗

Disruption of metapopulation structure effectively reduces Tasmanian devil facial tumour disease spread at the expense of abundance and genetic diversity

Metapopulation structure (i.e. the spatial arrangement of local populations and corridors between them) plays a fundamental role in the persistence of wildlife populations, but can also drive the spread of infectious diseases. While the disruption of metapopulation connectivity can reduce disease spread, it can also impair host resilience by disrupting gene flow and colonisation dynamics. Thus, a pressing challenge for many wildlife populations is to elucidate whether the benefits of disease management methods that reduce metapopulation connectivity outweigh the associated risks. Directly transmissible cancers are clonal malignant cell lines capable to spread through host populations without immune recognition, when susceptible and infected hosts become in close contact. Using an individual-based metapopulation model we investigate the effects of the interplay between host dispersal, disease transmission rate and inter-individual contact distance for transmission (determining within-population mixing) on the spread and persistence of a transmissible cancer, Tasmanian devil facial tumour disease (DFTD), from local to regional scales. Further, we explore population isolation scenarios to devise management strategies to mitigate disease spread. Disease spread, and the ensuing population declines, are synergistically determined by individuals dispersal, disease transmission rate and within-population mixing. Low to intermediate transmission rates can be magnified by high dispersal and inter-individual transmission distance. Once disease transmission rate is high, dispersal and inter-individual contact distance do not impact the outcome of the disease transmission dynamics. Isolation of local populations effectively reduced metapopulation-level disease prevalence but caused severe declines in metapopulation size and genetic diversity. The relative position of managed (i.e. isolated) populations within the metapopulation had a significant effect on disease prevalence, highlighting the importance of considering metapopulation structure when implementing metapopulation-scale disease control measures. Our findings suggests that population isolation is not an ideal management method for preventing disease spread in species inhabiting already fragmented landscapes, where genetic diversity and extinction risk are already a concern, such as the Tasmanian devil.

ecology↗

Historical and contemporary signatures of selection in response to transmissible cancer in the Tasmanian Devil (Sarcophilus harrisii)

Tasmanian devils (Sarcophilus harrisii) are evolving in response to a unique transmissible cancer, devil facial tumour disease (DFTD), first described in 1996. Persistence of wild populations and the recent emergence of a second independently evolved transmissible cancer suggest that transmissible cancers may be a recurrent feature in devils. Here we compared signatures of selection across temporal scales to determine whether genes or gene pathways under contemporary selection (6-8 generations) have also been subject to historical selection (65-85 million years), and test for recurrent selection in devils. First, we used a targeted sequencing approach, RAD-capture, to identify genomic regions subject to rapid evolution in approximately 2,500 devils in six populations as DFTD spread across the species range. We documented genome-wide contemporary evolution, including 186 candidate genes related to cell cycling and immune response. Then we used a molecular evolution approach to identify historical positive selection in devils compared to other marsupials and found evidence of selection in 1,773 genes. However, we found limited overlap across time scales, with historical selection detected in only 16 contemporary candidate genes, and no overlap in enriched functional gene sets. Our results are consistent with a novel, multi-locus evolutionary response of devils to DFTD. Our results can inform management actions to conserve adaptive potential of devils by identifying high priority targets for genetic monitoring and maintenance of functional diversity in managed populations.

evolutionary biology↗

Disease swamps molecular signatures of genetic-environmental associations to abiotic factors in Tasmanian devil (Sarcophilus harrisii) populations

Landscape genomics studies focus on identifying candidate genes under selection via spatial variation in abiotic environmental variables, but rarely by biotic factors such as disease. The Tasmanian devil (Sarcophilus harrisii) is found only on the environmentally heterogeneous island of Tasmania and is threatened with extinction by a nearly 100% fatal, transmissible cancer, devil facial tumor disease (DFTD). Devils persist in regions of long-term infection despite epidemiological model predictions of species extinction, suggesting possible adaptation to DFTD. Here, we test the extent to which spatial variation and genetic diversity are associated with the abiotic environment and/or by DFTD. We employ genetic-environment association (GEAs) analyses using a RAD-capture panel consisting of 6,886 SNPs from 3,286 individuals sampled pre- and post-disease arrival. Pre-disease, we find significant correlations of allele frequencies with environmental variables, including 349 unique loci linked to 64 genes, suggesting local adaptation to abiotic environment. Following DFTD arrival, however, we detected few of the pre-disease candidate loci, but instead frequencies of candidate loci linked to 14 genes correlated with disease prevalence. Loss of apparent signal of abiotic local adaptation following disease arrival suggests swamping by the strong selection imposed by DFTD. Further support for this result comes from the fact that post-disease candidate loci are in linkage disequilibrium with genes putatively involved in immune response, tumor suppression and apoptosis. This suggests the strength GEA associations of loci with the abiotic environment are swamped resulting from the rapid onset of a biotic selective pressure.

evolutionary biology↗

Tasman-PCR: A genetic diagnostic assay for Tasmanian devil facial tumour diseases

Tasmanian devils have spawned two transmissible cancer clones, known as devil facial tumour 1 (DFT1) and devil facial tumour 2 (DFT2). DFT1 and DFT2 are transmitted between animals by the transfer of allogeneic contagious cancer cells by biting, and both cause facial tumours. DFT1 and DFT2 tumours are grossly indistinguishable, but can be differentiated using histopathology, cytogenetics or genotyping of polymorphic markers. However, standard diagnostic methods require specialist skills and equipment and entail long processing times. Here, we describe Tasman-PCR: a simple PCR-based diagnostic assay that distinguishes DFT1 and DFT2 by amplification of DNA spanning tumour-specific interchromosomal translocations. We demonstrate the high sensitivity and specificity of this assay by testing DNA from 557 tumours and 818 normal devils. A temporal-spatial screen confirmed the reported geographic ranges of DFT1 and DFT2 and did not provide evidence of additional DFT clones. DFT2 affects disproportionately more males than females, and devils can be co-infected with DFT1 and DFT2. Overall, we present a PCR-based assay that delivers rapid, accurate and high-throughput diagnosis of DFT1 and DFT2. This tool provides an additional resource for devil disease management and may assist with ongoing conservation efforts.

genetics↗