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Amoebozoa include lineages of diverse ecology, behavior, and morphology. They are assumed to encompass members with the largest genome sizes of all living things, yet genomic studies in the group are limited. Trichosphaerium, a polymorphic, multinucleate, marine amoeba with a complicated life cycle, has puzzled experts for over a century. In an effort to explore the genomic diversity and investigate extraordinary behavior observed among the Amoebozoa, we used integrated omics approaches to study this enigmatic marine amoeba. Omics data, including single-cell transcriptomics and cytological data, demonstrate that Trichosphaerium sp. possesses the complete meiosis toolkit genes. These genes are expressed in life stages of the amoeba including medium and large cells. The life cycle of Trichosphaerium sp. involves asexual processes via binary fission and multiple fragmentation of giant cells, as well as sexual-like processes involving genes implicated in sexual reproduction and polyploidization. These findings are in stark contrast to a life cycle previously reported for this amoeba. Despite the extreme morphological plasticity observed in Trichosphaerium, our genomic data showed that populations maintain a species-level intragenomic variation. A draft genome of Trichosphaerium indicates elevated lateral gene transfer (LGT) from bacteria and giant viruses. Gene trafficking in Trichosphaerium is the highest within Amoebozoa and among the highest in microbial eukaryotes. 

Abstract. Systematic biases and coarse resolutions are major limitations ofcurrent precipitation datasets. Many deep learning (DL)-based studies havebeen conducted for precipitation bias correction and downscaling. However,it is still challenging for the current approaches to handle complexfeatures of hourly precipitation, resulting in the incapability ofreproducing small-scale features, such as extreme events. This studydeveloped a customized DL model by incorporating customized loss functions,multitask learning and physically relevant covariates to bias correct anddownscale hourly precipitation data. We designed six scenarios tosystematically evaluate the added values of weighted loss functions,multitask learning, and atmospheric covariates compared to the regular DLand statistical approaches. The models were trained and tested using theModern-era Retrospective Analysis for Research and Applications version 2(MERRA2) reanalysis and the Stage IV radar observations over the northerncoastal region of the Gulf of Mexico on an hourly time scale. We found thatall the scenarios with weighted loss functions performed notably better thanthe other scenarios with conventional loss functions and a quantilemapping-based approach at hourly, daily, and monthly time scales as well asextremes. Multitask learning showed improved performance on capturing finefeatures of extreme events and accounting for atmospheric covariates highlyimproved model performance at hourly and aggregated time scales, while theimprovement is not as large as from weighted loss functions. We show thatthe customized DL model can better downscale and bias correct hourlyprecipitation datasets and provide improved precipitation estimates at finespatial and temporal resolutions where regular DL and statistical methodsexperience challenges. 

Abstract To date, genomic analyses in amoebozoans have been mostly limited to model organisms or medically important lineages. Consequently, the vast diversity of Amoebozoa genomes remain unexplored. A draft genome of Cochliopodium minus , an amoeba characterized by extensive cellular and nuclear fusions, is presented. C. minus has been a subject of recent investigation for its unusual sexual behavior. Cochliopodium ’s sexual activity occurs during vegetative stage making it an ideal model for studying sexual development, which is sorely lacking in the group. Here we generate a C. minus draft genome assembly. From this genome, we detect a substantial number of lateral gene transfer (LGT) instances from bacteria (15%), archaea (0.9%) and viruses (0.7%) the majority of which are detected in our transcriptome data. We identify the complete meiosis toolkit genes in the C. minus genome, as well as the absence of several key genes involved in plasmogamy and karyogamy. Comparative genomics of amoebozoans reveals variation in sexual mechanism exist in the group. Similar to complex eukaryotes, C. minus (some amoebae) possesses Tyrosine kinases and duplicate copies of SPO11 . We report a first example of alternative splicing in a key meiosis gene and draw important insights on molecular mechanism of sex in C. minus using genomic and transcriptomic data. 

The evolution and diversity of the supergroup Amoebozoa is complex and poorly understood. The supergroup encompasses predominantly amoeboid lineages characterized by extreme diversity in phenotype, behavior and genetics. The study of natural selection, a driving force of diversification, within and among species of Amoebozoa will play a crucial role in understanding the evolution of the supergroup. In this study, we searched for traces of natural selection based on a set of highly conserved protein-coding genes in a phylogenetic framework from a broad sampling of amoebozoans. Using these genes, we estimated substitution rates and inferred patterns of selective pressure in lineages and sites with various models. We also examined the effect of selective pressure on codon usage bias and potential correlations with observed biological traits and habitat. Results showed large heterogeneity of selection across lineages of Amoebozoa, indicating potential species-specific optimization of adaptation to their diverse ecological environment. Overall, lineages in Tubulinea had undergone stronger purifying selection with higher average substitution rates compared to Discosea and Evosea. Evidence of adaptive evolution was observed in some representative lineages and in a gene (Rpl7a) within Evosea, suggesting potential innovation and beneficial mutations in these lineages. Our results revealed that members of the fast-evolving lineages, Entamoeba and Cutosea, all underwent strong purifying selection but had distinct patterns of codon usage bias. For the first time, this study revealed an overall pattern of natural selection across the phylogeny of Amoebozoa and provided significant implications on their distinctive evolutionary processes. 

Abstract Filtering facepiece respirators (FFRs) provide effective protection against diseases spread through airborne infectious droplets and particles. The widespread use of FFRs during the COVID-19 pandemic has not only led to supply shortages, but the disposal of single-use facemasks also threatens the environment with a new kind of plastic pollution. While limited reuse of filtering facepiece respirators has been permitted as a crisis capacity strategy, there are currently no standard test methods available for decontamination before their repeated use. The decontamination of respirators can compromise the structural and functional integrity by reducing the filtration efficiency and breathability. Digital segmentation of X-ray microcomputed tomography (microCT) scans of the meltblown nonwoven layers of a specific N95 respirator model (Venus-4400) after treatment with one and five cycles of liquid hydrogen peroxide, ultraviolet radiation, moist heat, and aqueous soap solution enabled us to perform filtration simulations of decontaminated respirators. The computed filtration efficiencies for 0.3 µm particles agreed well with experimental measurements, and the distribution of particle penetration depths was correlated with the structural changes resulting from decontamination. The combination of X-ray microCT imaging with numerical simulations thus provides a strategy for quantitative evaluation of the effectiveness of decontamination treatments for a specific respirator model.