Holographic reconstruction enhancement via unpaired image-to-image translation.

Digital holographic microscopy is an imaging process that encodes the 3D information of a sample into a single 2D hologram. The holographic reconstruction that decodes the hologram is conventionally based on the diffraction formula and involves various iterative steps in order to recover the lost phase information of the hologram. In the past few years, the deep-learning-based model has shown great potential to perform holographic reconstruction directly on a single hologram. However, preparing a large and high-quality dataset to train the models remains a challenge, especially when the holographic reconstruction images that serve as ground truth are difficult to obtain and can have a deteriorated quality due to various interferences of the imaging device. A cycle generative adversarial network is first trained with unpaired brightfield microscope images to restore the visual quality of the holographic reconstructions. The enhanced holographic reconstructions then serve as ground truth for the supervised learning of a U-Net that performs the holographic reconstruction on a single hologram. The proposed method was evaluated on plankton images and could also be applied to achieve super-resolution or colorization of the holographic reconstructions.

The Active Microbiota of the Eggs and the Nauplii of the Pacific Blue Shrimp Litopenaeus stylirostris Partially Shaped by a Potential Vertical Transmission.

The many ecological niches present in an organism harbor distinct microorganisms called microbiota. Different factors can influence the establishment of these commensal microbial communities. In a previous article, we have concluded that some bacterial lineages associated with the early larval stages of the Pacific blue shrimp Litopenaeus stylirostris could be acquired from the breeders via a potential vertical transmission. The present study was conducted in order to investigate this hypothesis. Using HiSeq sequencing of the V4 region of 16S rRNA gene, we analyzed the active microbiota associated with the eggs and the nauplii of L. stylirsotris as well as with the reproductive organs of their breeders. Microbial communities associated with the rearing water were also considered to discriminate environmental microbial lineages. Using these analyses, we highlight a set of core bacterial families present in all samples and composed of members of Colwelliaceae, Alteromonadaceae, Pseudoalteromonadaceae, Saccharospirillaceae, Oceanospirillaceae, Vibrionaceae, Burkholderiaceae, Rhodobacteraceae, Flavobacteraceae, and Corynebacteriaceae; showing the importance of the environment in the establishment of the larval microbiota. We also present specific bacteria affiliated to the Arcobacteraceae, Rhodobacteraceae, Comamonadaceae, and Colwelliaceae families, which were only found in the breeders and their offspring strengthening the hypothesis of a potential vertical transmission shaping the active microbiota of the eggs and the nauplii of L. stylirostris.

Wolbachia detection in Aedes aegypti using MALDI-TOF MS coupled to artificial intelligence.

The mosquito Aedes aegypti is the major vector of arboviruses like dengue, Zika and chikungunya viruses. Attempts to reduce arboviruses emergence focusing on Ae. aegypti control has proven challenging due to the increase of insecticide resistances. An emerging strategy which consists of releasing Ae. aegypti artificially infected with Wolbachia in natural mosquito populations is currently being developed. The monitoring of Wolbachia-positive Ae. aegypti in the field is performed in order to ensure the program effectiveness. Here, the reliability of the Matrix­Assisted Laser Desorption Ionization­Time Of Flight (MALDI­TOF) coupled with the machine learning methods like Convolutional Neural Network (CNN) to detect Wolbachia in field Ae. aegypti was assessed for the first time. For this purpose, laboratory reared and field Ae. aegypti were analyzed. The results showed that the CNN recognized Ae. aegypti spectral patterns associated with Wolbachia-infection. The MALDI-TOF coupled with the CNN (sensitivity = 93%, specificity = 99%, accuracy = 97%) was more efficient than the loop-mediated isothermal amplification (LAMP), and as efficient as qPCR for Wolbachia detection. It therefore represents an interesting method to evaluate the prevalence of Wolbachia in field Ae. aegypti mosquitoes.

Potential lineage transmission within the active microbiota of the eggs and the nauplii of the shrimp Litopenaeus stylirostris: possible influence of the rearing water and more.

BACKGROUND: Microbial communities associated with animals are known to be key elements in the development of their hosts. In marine environments, these communities are largely under the influence of the surrounding water. In aquaculture, understanding the interactions existing between the microbiotas of farmed species and their rearing environment could help establish precise bacterial management. METHOD: In light of these facts, we studied the active microbial communities associated with the eggs and the nauplii of the Pacific blue shrimp (Litopenaeus stylirostris) and their rearing water. All samples were collected in September 2018, November 2018 and February 2019. After RNA extractions, two distinct Illumina HiSeq sequencings were performed. Due to different sequencing depths and in order to compare samples, data were normalized using the Count Per Million method. RESULTS: We found a core microbiota made of taxa related to Aestuariibacter, Alteromonas, Vibrio, SAR11, HIMB11, AEGEAN 169 marine group and Candidatus Endobugula associated with all the samples indicating that these bacterial communities could be transferred from the water to the animals. We also highlighted specific bacterial taxa in the eggs and the nauplii affiliated to Pseudomonas, Corynebacterium, Acinetobacter, Labrenzia, Rothia, Thalassolituus, Marinobacter, Aureispira, Oleiphilus, Profundimonas and Marinobacterium genera suggesting a possible prokaryotic vertical transmission from the breeders to their offspring. This study is the first to focus on the active microbiota associated with early developmental stages of a farmed shrimp species and could serve as a basis to comprehend the microbial interactions involved throughout the whole rearing process.

A regionally scalable habitat typology for assessing benthic habitats and fish communities: Application to New Caledonia reefs and lagoons.

Scalable assessments of biodiversity are required to successfully and adaptively manage coastal ecosystems. Assessments must account for habitat variations at multiple spatial scales, including the small scales (<100 m) at which biotic and abiotic habitat components structure the distribution of fauna, including fishes. Associated challenges include achieving consistent habitat descriptions and upscaling from in situ-monitored stations to larger scales. We developed a methodology for (a) determining habitat types consistent across scales within large management units, (b) characterizing heterogeneities within each habitat, and (c) predicting habitat from new survey data. It relies on clustering techniques and supervised classification rules and was applied to a set of 3,145 underwater video observations of fish and benthic habitats collected in all reef and lagoon habitats around New Caledonia. A baseline habitat typology was established with five habitat types clearly characterized by abiotic and biotic attributes. In a complex mosaic of habitats, habitat type is an indispensable covariate for explaining spatial variations in fish communities. Habitat types were further described by 26 rules capturing the range of habitat features encountered. Rules provided intuitive habitat descriptions and predicted habitat type for new monitoring observations, both straightforwardly and with known confidence. Images are convenient for interacting with managers and stakeholders. Our scheme is (a) consistent at the scale of New Caledonia reefs and lagoons (1.4 million km2) and (b) ubiquitous by providing data in all habitats, for example, showcasing a substantial fish abundance in rarely monitored soft-bottom habitats. Both features must be part of an ecosystem-based monitoring strategy relevant for management. This is the first study applying data mining techniques to in situ measurements to characterize coastal habitats over regional-scale management areas. This approach can be applied to other types of observations and other ecosystems to characterize and predict local ecological assets for assessments at larger scales.

Surveying shrimp aquaculture pond activity using multitemporal VHSR satellite images - case study from the Perancak estuary, Bali, Indonesia.

From the 1980's, Indonesian shrimp production has continuously increased through a large expansion of cultured areas and an intensification of the production. As consequences of diseases and environmental degradations linked to this development, there are currently 250,000ha of abandoned ponds in Indonesia. To implement effective procedure to undertake appropriate aquaculture ecosystem assessment and monitoring, an integrated indicator based on four criteria using very high spatial optical satellite images, has been developed to discriminate active from abandoned ponds. These criteria were: presence of water, aerator, feeding bridge and vegetation. This indicator has then been applied to the Perancak estuary, a production area in decline, to highlight the abandonment dynamic between 2001 and 2015. Two risk factors that could contribute to explain dynamics of abandonment were identified: climate conditions and pond locations within the estuary, suggesting that a spatial approach should be integrated in planning processes to operationalize pond rehabilitation.