Assessment of the microbial communities associated with white syndrome and brown jelly syndrome in aquarium corals

Bacterial and ciliate assemblages associated with aquarium corals displaying white syndrome (WS) and brown jelly syndrome (BJS) were investigated. Healthy (n = 10) and diseased corals (WS n = 18; BJS n = 3) were analysed for 16S rRNA gene bacterial diversity, total bacterial abundance and vibrio-specific 16S rRNA gene abundance. This was conducted alongside analysis of 18S rRNA gene sequenc-ing targeting ciliates, a group of organisms largely overlooked for their potential as causal agents of coral disease. Despite significant differences between healthy and diseased corals in their 16S rRNA gene bacterial diversity, total bacterial abundance and vibrio-specific rRNA gene abundance, no domi-nant bacterial ribotypes were found consistently within the diseased samples. In contrast, one ciliate morphotype, named Morph 3 in this study (GenBank Accession Numbers JF831358 for the ciliate isolated from WS and JF831359 for the ciliate isolated from BJS) was observed to burrow into and underneath the coral tissues at the disease lesion in both disease types and contained algal endosym-bionts indicative of coral tissue ingestion. This ciliate was observed in larger numbers in BJS compared to WS, giving rise to the characteristic jelly like substance in BJS. Morph 3 varied by only 1 bp over 549 bp from the recently described Morph 1 ciliate (GenBank Accession No. JN626268), which has been shown to be present in field samples of WS and Brown Band Disease (BrB) in the Indo-Pacific. This result indicates a close relationship between these aquarium diseases and those observed in the wild

Experimental antibiotic treatment identifies potential pathogens of white band disease in the endangered Caribbean coral Acropora cervicornis

Coral diseases have been increasingly reported over the past few decades and are a major contributor to coral decline worldwide. The Caribbean, in particular, has been noted as a hotspot for coral disease, and the aptly named white syndromes have caused the decline of the dominant reef building corals throughout their range. White band disease (WBD) has been implicated in the dramatic loss of Acropora cervicornis and Acropora palmata since the 1970s, resulting in both species being listed as critically endangered on the International Union for Conservation of Nature Red list. The causal agent of WBD remains unknown, although recent studies based on challenge experiments with filtrate from infected hosts concluded that the disease is probably caused by bacteria. Here, we report an experiment using four different antibiotic treatments, targeting different members of the disease-associated microbial community. Two antibiotics, ampicillin and paromomycin, arrested the disease completely, and by comparing with community shifts brought about by treatments that did not arrest the disease, we have identified the likely candidate causal agent or agents of WBD. Our interpretation of the experimental treatments is that one or a combination of up to three specific bacterial types, detected consistently in diseased corals but not detectable in healthy corals, are likely causal agents of WBD. In addition, a histophagous ciliate (Philaster lucinda) identical to that found consistently in association with white syndrome in Indo-Pacific acroporas was also consistently detected in allWBDsamples and absent in healthy coral. Treatment with metronidazole reduced it to below detection limits, but did not arrest the disease. However, the microscopic disease signs changed, suggesting a secondary role in disease causation for this ciliate. In future studies to identify a causal agent ofWBDvia tests of Henle–Koch’s postulates, it will be vital to experimentally control for populations of the other potential pathogens identified in this study

Coral diseases in aquaria and in nature

Many reef coral diseases have been described affecting corals in the wild, several of which have been associated with causal agents based on experimental inoculation and testing of Koch’s postulates. In the aquarium industry, many coral diseases and pathologies are known from the grey literature but as yet these have not been systematically described and the relationship to known diseases in the wild is difficult to determine. There is therefore scope to aid the maintenance and husbandry of corals in aquaria by informing the field of the scientifically described wild diseases, if these can be reliably related. Conversely, since the main driver to identifying coral diseases in aquaria is to select an effective treatment, the lessons learnt by aquarists on which treatments work with particular syndromes provides invaluable evidence for determining the causal agents. Such treatments are not commonly sought by scientists working in the natural environment due the cost and potential environmental impacts of the treatments. Here we review both wild and aquarium diseases and attempt to relate the two. Many important aquarium diseases could not be reconciled to those in the wild. In one case, however, namely that of the ciliate Helicostoma sp. as a causal agent of brown jelly syndrome in aquarium corals, there may be similarities with pathogenic agents of the wild coral diseases, such as white syndrome and brown band syndrome. We propose that Helicostoma is actually a misnomer, but improved understanding of this pathogen and others could benefit both fields. Improved practices in aquarium maintenance and husbandry would also benefit natural environments by reducing the scale of wild harvest and improving the potential for coral culture, both for the aquarium industry and for rehabilitation programmes

Branchpoint translocation by fork remodelers as a general mechanism of R-loop removal.

Co-transcriptional R loops arise from stalling of RNA polymerase, leading to the formation of stable DNA:RNA hybrids. Unresolved R loops promote genome instability but are counteracted by helicases and nucleases. Here, we show that branchpoint translocases are a third class of R-loop-displacing enzyme in vitro. In cells, deficiency in the Fanconi-anemia-associated branchpoint translocase FANCM causes R-loop accumulation, particularly after treatment with DNA:RNA-hybrid-stabilizing agents. This correlates with FANCM localization at R-loop-prone regions of the genome. Moreover, other branchpoint translocases associated with human disease, such as SMARCAL1 and ZRANB3, and those from lower organisms can also remove R loops in vitro. Branchpoint translocases are more potent than helicases in resolving R loops, indicating their evolutionary important role in R-loop suppression. In human cells, FANCM, SMARCAL1, and ZRANB3 depletion causes additive effects on R-loop accumulation and DNA damage. Our work reveals a mechanistic basis for R-loop displacement that is linked to genome stability

Vertical distribution and diel patterns of zooplankton abundance and biomass at Conch Reef, Florida Keys (USA)

Zooplankton play an important role in the trophic dynamics of coral reef ecosystems. Detailed vertical and temporal distribution and biomass of zooplankton were evaluated at four heights off the bottom and at six times throughout the diel cycle over a coral reef in the Florida Keys (USA). Zooplankton abundance averaged 4396 ± 1949 SD individuals m−3, but temporal and spatial distributions varied for individual zooplankton taxa by time of day and by height off the bottom. Copepods comprised 93–96% of the abundance in the samples. Taxon-based zooplankton CHN values paired with abundance data were used to estimate biomass. Average daily biomass ranged from 3.1 to 21.4 mg C m−3 and differed by both height off the bottom and by time of day. While copepods were the numerically dominant organisms, their contribution to biomass was only 35% of the total zooplankton biomass. Our findings provide important support for the new emerging paradigm of how zooplankton are distributed over reefs

Fine-Tuning Heat Stress Algorithms to Optimise Global Predictions of Mass Coral Bleaching

Increasingly intense marine heatwaves threaten the persistence of many marine ecosystems. Heat stress-mediated episodes of mass coral bleaching have led to catastrophic coral mortality globally. Remotely monitoring and forecasting such biotic responses to heat stress is key for effective marine ecosystem management. The Degree Heating Week (DHW) metric, designed to monitor coral bleaching risk, reflects the duration and intensity of heat stress events and is computed by accumulating SST anomalies (HotSpot) relative to a stress threshold over a 12-week moving window. Despite significant improvements in the underlying SST datasets, corresponding revisions of the HotSpot threshold and accumulation window are still lacking. Here, we fine-tune the operational DHW algorithm to optimise coral bleaching predictions using the 5 km satellite-based SSTs (CoralTemp v3.1) and a global coral bleaching dataset (37,871 observations, National Oceanic and Atmospheric Administration). After developing 234 test DHW algorithms with different combinations of the HotSpot threshold and accumulation window, we compared their bleaching prediction ability using spatiotemporal Bayesian hierarchical models and sensitivity–specificity analyses. Peak DHW performance was reached using HotSpot thresholds less than or equal to the maximum of monthly means SST climatology (MMM) and accumulation windows of 4–8 weeks. This new configuration correctly predicted up to an additional 310 bleaching observations globally compared to the operational DHW algorithm, an improved hit rate of 7.9%. Given the detrimental impacts of marine heatwaves across ecosystems, heat stress algorithms could also be fine-tuned for other biological systems, improving scientific accuracy, and enabling ecosystem governance

Risk of death among people with rare autoimmune diseases compared with the general population in England during the 2020 COVID-19 pandemic

Objectives: To quantify the risk of death among people with rare autoimmune rheumatic diseases (RAIRD) during the UK 2020 COVID-19 pandemic compared with the general population, and compared with their pre-COVID risk. Methods: We conducted a cohort study in Hospital Episode Statistics for England from 2003 onwards, and linked data from the NHS Personal Demographics Service. We used ONS published data for general population mortality rates. Results: We included 168 691 people with a recorded diagnosis of RAIRD alive on 1 March 2020. Their median age was 61.7 (IQR 41.5-75.4) years, and 118 379 (70.2%) were female. Our case ascertainment methods had a positive predictive value of 85%. A total of 1815 (1.1%) participants died during March and April 2020. The age-standardized mortality rate (ASMR) among people with RAIRD (3669.3; 95% CI: 3500.4, 3838.1 per 100 000 person-years) was 1.44 (95% CI: 1.42, 1.45) times higher than the average ASMR during the same months of the previous 5 years, whereas in the general population of England it was 1.38 times higher. Age-specific mortality rates in people with RAIRD compared with the pre-COVID rates were higher from the age of 35 upwards, whereas in the general population the increased risk began from age 55 upwards. Women had a greater increase in mortality rates during COVID-19 compared with men. Conclusion: The risk of all-cause death is more prominently raised during COVID-19 among people with RAIRD than among the general population. We urgently need to quantify how much risk is due to COVID-19 infection and how much is due to disruption to health-care services

Validation of methods to identify people with idiopathic inflammatory myopathies using hospital episode statistics

ObjectiveHospital episode statistics (HES) are routinely recorded at every hospital admission within the National Health Service (NHS) in England. This study validates diagnostic ICD-10 codes within HES as a method of identifying cases of idiopathic inflammatory myopathies (IIMs).MethodsAll inpatient admissions at one NHS Trust between 2010 and 2020 with relevant diagnostic ICD-10 codes were extracted from HES. Hospital databases were used to identify all outpatients with IIM, and electronic care records were reviewed to confirm coding accuracy. Total hospital admissions were calculated from NHS Digital reports. The sensitivity and specificity of each code and code combinations were calculated to develop an optimal algorithm. The optimal algorithm was tested in a sample of admissions at another NHS Trust.ResultsOf the 672 individuals identified by HES, 510 were confirmed to have IIM. Overall, the positive predictive value (PPV) was 76% and sensitivity 89%. Combination algorithms achieved PPVs between 89 and 94%. HES can also predict the presence of IIM-associated interstitial lung disease (ILD) with a PPV of 79% and sensitivity of 71%. The optimal algorithm excluded children (except JDM code M33.0), combined M33.0, M33.1, M33.9, M36.0, G72.4, M60.8 and M33.2, and included M60.9 only if it occurred alongside an ILD code (J84.1, J84.9 or J99.1). This produced a PPV of 88.9% and sensitivity of 84.2%. Retesting this algorithm at another NHS Trust confirmed a high PPV (94.4%).ConclusionIIM ICD-10 code combinations in HES have high PPVs and sensitivities. Algorithms tested in this study could be applied across all NHS Trusts to enable robust and cost-effective whole-population research into the epidemiology of IIM