Microbial communities associated with the parasitic copepod Lepeophtheirus salmonis.

Lepeophtheirus salmonis is a naturally occurring marine parasite of salmonid fishes in the Northern hemisphere, and a major problem in salmonid aquaculture. In addition to the direct effects on host fish, L. salmonis may act as a vector for diseases. Here, the microbial community of L. salmonis recovered from whole genome shotgun sequencing was compared between lice sampled from both the Atlantic and the Pacific, laboratory-reared and wild lice, in addition to lice displaying resistance towards chemical treatments. The analysis shows clear differences in the metagenomic composition between the Atlantic and the Pacific Ocean, whereas the resistance status of the L. salmonis or the cultivation did not have significant impact.submittedVersio

A novel method for the rapid enumeration of planktonic salmon lice in a mixed zooplankton assemblage using fluorescence

The relative rarity of the planktonic larval stages of salmon lice in comparison to other animals captured in a zooplankton assemblage is an obstacle to estimating their abundance and distribution. Due to the labour intensiveness of standard plankton sorting approaches, the planktonic stages of salmon lice remain understudied and unmonitored despite their importance to the spread of the parasite between salmon farms and to wild salmonids. Alternative methods of identification have been investigated and in a previous study a fluorescence signal was identified. Using filters to target that signal with fluorescence microscopy (excitation/emission wavelengths of 470/525 nm), the salmon louse has a fluorescence intensity 2.4 times greater than non-target animals, which distinguishes it from the zooplankton assemblage and enables rapid enumeration. Here, we present a novel method for the enumeration of planktonic salmon lice larvae, nauplius and copepodid stages, in a mixed zooplankton sample using fluorescence-aided microscopy. Performance of the method was evaluated with a blind trial which found a median accuracy of 81.8% and a mean sample processing time of 31 min. Compared with previously published findings, the novel method provides satisfactory accuracy and enumeration that is more than 20 times faster than traditional light microscopy approaches. Factors influencing the performance of the method are identified and recommendations are made for targeted sampling and automated enumeration

The salmon louse genome: Copepod features and parasitic adaptations

Copepods encompass numerous ecological roles including parasites, detrivores and phytoplankton grazers. Nonetheless, copepod genome assemblies remain scarce. Lepeophtheirus salmonis is an economically and ecologically important ectoparasitic copepod found on salmonid fish. We present the 695.4 Mbp L. salmonis genome assembly containing ≈60% repetitive regions and 13,081 annotated protein-coding genes. The genome comprises 14 autosomes and a ZZ-ZW sex chromosome system. Assembly assessment identified 92.4% of the expected arthropod genes. Transcriptomics supported annotation and indicated a marked shift in gene expression after host attachment, including apparent downregulation of genes related to circadian rhythm coinciding with abandoning diurnal migration. The genome shows evolutionary signatures including loss of genes needed for peroxisome biogenesis, presence of numerous FNII domains, and an incomplete heme homeostasis pathway suggesting heme proteins to be obtained from the host. Despite repeated development of resistance against chemical treatments L. salmonis exhibits low numbers of many genes involved in detoxification.publishedVersio

Predicting Choroidal Nevus Transformation to Melanoma Using Machine Learning

PURPOSE: To develop and validate machine learning (ML) models to predict choroidal nevus transformation to melanoma based on multimodal imaging at initial presentation. DESIGN: Retrospective multicenter study. PARTICIPANTS: Patients diagnosed with choroidal nevus on the Ocular Oncology Service at Wills Eye Hospital (2007-2017) or Mayo Clinic Rochester (2015-2023). METHODS: Multimodal imaging was obtained, including fundus photography, fundus autofluorescence, spectral domain OCT, and B-scan ultrasonography. Machine learning models were created (XGBoost, LGBM, Random Forest, Extra Tree) and optimized for area under receiver operating characteristic curve (AUROC). The Wills Eye Hospital cohort was used for training and testing (80% training-20% testing) with fivefold cross validation. The Mayo Clinic cohort provided external validation. Model performance was characterized by AUROC and area under precision-recall curve (AUPRC). Models were interrogated using SHapley Additive exPlanations (SHAP) to identify the features most predictive of conversion from nevus to melanoma. Differences in AUROC and AUPRC between models were tested using 10 000 bootstrap samples with replacement and results. MAIN OUTCOME MEASURES: Area under receiver operating curve and AUPRC for each ML model. RESULTS: There were 2870 nevi included in the study, with conversion to melanoma confirmed in 128 cases. Simple AI Nevus Transformation System (SAINTS; XGBoost) was the top-performing model in the test cohort [pooled AUROC 0.864 (95% confidence interval (CI): 0.864-0.865), pooled AUPRC 0.244 (95% CI: 0.243-0.246)] and in the external validation cohort [pooled AUROC 0.931 (95% CI: 0.930-0.931), pooled AUPRC 0.533 (95% CI: 0.531-0.535)]. Other models also had good discriminative performance: LGBM (test set pooled AUROC 0.831, validation set pooled AUROC 0.815), Random Forest (test set pooled AUROC 0.812, validation set pooled AUROC 0.866), and Extra Tree (test set pooled AUROC 0.826, validation set pooled AUROC 0.915). A model including only nevi with at least 5 years of follow-up demonstrated the best performance in AUPRC (test: pooled 0.592 (95% CI: 0.590-0.594); validation: pooled 0.656 [95% CI: 0.655-0.657]). The top 5 features in SAINTS by SHAP values were: tumor thickness, largest tumor basal diameter, tumor shape, distance to optic nerve, and subretinal fluid extent. CONCLUSIONS: We demonstrate accuracy and generalizability of a ML model for predicting choroidal nevus transformation to melanoma based on multimodal imaging. FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article

White paper on ophthalmic imaging for choroidal nevus identification and transformation into Melanoma

Purpose: To discuss the evolution of noninvasive diagnostic methods in the identification of choroidal nevus and determination of risk factors for malignant transformation as well as introduce the novel role that artificial intelligence (AI) can play in the diagnostic process. Methods: White paper. Results: Longstanding diagnostic methods to stratify benign choroidal nevus from choroidal melanoma and to further determine the risk for nevus transformation into melanoma have been dependent on recognition of key clinical features by ophthalmic examination. These risk factors have been derived from multiple large cohort research studies over the past several decades and have garnered widespread use throughout the world. More recent publications have applied ocular diagnostic testing (fundus photog-raphy, ultrasound examination, autofluorescence, and optical coherence tomography) to identify risk factors for the malignant transformation of choroidal nevus based on multimodal imaging features. The widespread usage of ophthalmic imaging systems to identify and follow choroidal nevus, in conjunction with the characterization of malignant transformation risk factors via diagnostic imaging, presents a novel path to apply AI. Conclusions: AI applied to existing ophthalmic imaging systems could be used for both identification of choroidal nevus and as a tool to aid in earlier detection of transformation to malignant melanoma. Translational Relevance: Advances in AI models applied to ophthalmic imaging systems have the potential to improve patient care, because earlier detection and treatment of melanoma has been proven to improve long-term clinical outcomes

Genomic Resources for Sea Lice: Analysis of ESTs and Mitochondrial Genomes

Sea lice are common parasites of both farmed and wild salmon. Salmon farming constitutes an important economic market in North America, South America, and Northern Europe. Infections with sea lice can result in significant production losses. A compilation of genomic information on different genera of sea lice is an important resource for understanding their biology as well as for the study of population genetics and control strategies. We report on over 150,000 expressed sequence tags (ESTs) from five different species (Pacific Lepeophtheirus salmonis (49,672 new ESTs in addition to 14,994 previously reported ESTs), Atlantic L. salmonis (57,349 ESTs), Caligus clemensi (14,821 ESTs), Caligus rogercresseyi (32,135 ESTs), and Lernaeocera branchialis (16,441 ESTs)). For each species, ESTs were assembled into complete or partial genes and annotated by comparisons to known proteins in public databases. In addition, whole mitochondrial (mt) genome sequences of C. clemensi (13,440 bp) and C. rogercresseyi (13,468 bp) were determined and compared to L. salmonis. Both nuclear and mtDNA genes show very high levels of sequence divergence between these ectoparastic copepods suggesting that the different species of sea lice have been in existence for 37–113 million years and that parasitic association with salmonids is also quite ancient. Our ESTs and mtDNA data provide a novel resource for the study of sea louse biology, population genetics, and control strategies. This genomic information provides the material basis for the development of a 38K sea louse microarray that can be used in conjunction with our existing 44K salmon microarray to study host–parasite interactions at the molecular level. This report represents the largest genomic resource for any copepod species to date

Environmental effects of ozone depletion, UV radiation and interactions with climate change : UNEP Environmental Effects Assessment Panel, update 2017

Peer reviewe

Effect of temperature on development rate and egg production in Caligus elongatus and other sea louse species

The sea louse Caligus elongatus (Siphonostomatoida, Caligidae) is a generalist ectoparasite commonly found on farmed salmonids in the Atlantic Ocean. Together with the salmon louse Lepeophtheirus salmonis and the Chilean sea louse Caligus rogercresseyi, they represent a major challenge to sustainable farming of Atlantic salmon Salmo salar. Here, the development rate, egg production, and copepodid survival time of C. elongatus are described at 6, 9, 12, and 15°C, and compared to available data for L. salmonis and C. rogercresseyi in a seminal attempt to qualitatively compare how these life-history traits and epidemiological factors vary among the 3 caligid sea louse species. A development model for C. elongatus was established by applying a constant scaling factor to the published model for L. salmonis and compared to the data obtained. The model assumes that caligid sea lice with similar zones of temperature tolerance share a common basic physiology, and that their rate of development is equally affected by changing temperatures within the interval where their temperature tolerances overlap. Present data, and data from the literature, suggest that C. elongatus develops to adult at approximately 63% of the time required by L. salmonis females and, compared to L. salmonis, they produce about 1/3 of the eggs per day over the temperature interval studied. This study represents a new experimental approach for establishing caligid development models and demonstrates how important life-history parameters can be scaled by constants and used as temperature-independent measures to characterize and compare the biology and epidemiology of sea lice species

Localization and transcription patterns of LsVasa, a molecular marker of germ cells in<i>Lepeophtheirus salmonis</i>(Krøyer)

Dalvin, Sussie, Nilsen, Frank, Skern-Mauritzen, Rasmus (2013): Localization and transcription patterns of LsVasa, a molecular marker of germ cells in Lepeophtheirus salmonis (Krøyer). Journal of Natural History 47 (5-12): 889-900, DOI: 10.1080/00222933.2012.738830, URL: http://dx.doi.org/10.1080/00222933.2012.73883