Self-controlled Sequencing Suggests that Somatic Mutations of Signaling, Transcription and Tumor Suppression Genes are a Precondition for AML Transformation in MDS

Background The transformation biology of secondary AML from MDS is still not fully understood. Here, we performed a large cohort of paired self-controlled sequences including target, whole-exome and single cell sequencing to search AML transformation-related mutations (TRMs). Methods 39 target genes from paired samples from 72 patients with MDS who had undergone AML transformation were analyzed by next generation target sequencing. Whole exome and single-cell RNA sequencing were used to verify the dynamics of transformation. Results The target sequencing results showed that sixty-four out of the 72 (88.9%) patients presented presumptive TRMs involving activated signaling, transcription factors, or tumor suppressors. Of the 64 patients, most of TRMs (62.5%, 40 cases) emerged at the leukemia transformation point. All three of the remaining eight patients analyzed by paired whole exome sequencing showed TRMs which are not included in the reference targets. No patient with MDS developed into AML only by acquiring mutations involved in epigenetic modulation or RNA splicing. Single-cell sequencing in one pair sample indicated that the activated cell signaling route was related to TRMs which take place prior to phenotypic development. Of note, target sequencing defined TRMs were limited to a small set of seven genes (in the order: NRAS/KRAS, CEBPA, TP53, FLT3, CBL, PTPN11 and RUNX1, accounted for nearly 90.0% of the TRMs). Conclusions Somatic mutations involving in signaling, transcription factors, or tumor suppressors appeared to be a precondition for AML transformation from MDS. The TRMs may be considered as new therapy targets.

Genomic insights into the phylogeny and biomass-degrading enzymes of rumen ciliates

Understanding the biodiversity and genetics of the gut microbiome has important implications for host physiology. One underexplored and elusive group is ciliated protozoa, which play crucial roles in regulating gut microbial interactions. Integrating single-cell sequencing and an assembly-and-identification pipeline, we acquired 52 high-quality ciliate genomes of 22 rumen morphospecies for all major abundant clades. With these genomes, we firstly resolved the taxonomic and phylogenetic framework that reclassified them into 19 species spanning 13 genera and reassigned the genus Dasytricha from Isotrichidae to a new family Dasytrichidae. Via extensive horizontal gene transfer and gene family expansion, rumen ciliates possess a broad array of enzymes to synergistically degrade plant and microbial carbohydrates. In particular, ~80% of the degrading enzymes in Diplodiniinae and Ophryoscolecinae act on plant cell wall, and the high activities of their cellulase, xylanase and lysozyme reflect the potential of ciliate enzymes for biomass-conversion. Additionally, the new ciliate dataset greatly facilitated the rumen metagenomic analyses by allowing ~12% of reads to be classified.

Interpretable Autoencoders Trained on Single Cell Sequencing Data Can Transfer Directly to Data from Unseen Tissues

Autoencoders have been used to model single-cell mRNA-sequencing data with the purpose of denoising, visualization, data simulation, and dimensionality reduction. We, and others, have shown that autoencoders can be explainable models and interpreted in terms of biology. Here, we show that such autoencoders can generalize to the extent that they can transfer directly without additional training. In practice, we can extract biological modules, denoise, and classify data correctly from an autoencoder that was trained on a different dataset and with different cells (a foreign model). We deconvoluted the biological signal encoded in the bottleneck layer of scRNA-models using saliency maps and mapped salient features to biological pathways. Biological concepts could be associated with specific nodes and interpreted in relation to biological pathways. Even in this unsupervised framework, with no prior information about cell types or labels, the specific biological pathways deduced from the model were in line with findings in previous research. It was hypothesized that autoencoders could learn and represent meaningful biology; here, we show with a systematic experiment that this is true and even transcends the training data. This means that carefully trained autoencoders can be used to assist the interpretation of new unseen data.

Monospecific and bispecific monoclonal SARS-CoV-2 neutralizing antibodies that maintain potency against B.1.617

COVID-19 pathogen SARS-CoV-2 has infected hundreds of millions and caused over 5 million deaths to date. Although multiple vaccines are available, breakthrough infections occur especially by emerging variants. Effective therapeutic options such as monoclonal antibodies (mAbs) are still critical. Here, we report the development, cryo-EM structures, and functional analyses of mAbs that potently neutralize SARS-CoV-2 variants of concern. By high-throughput single cell sequencing of B cells from spike receptor binding domain (RBD) immunized animals, we identified two highly potent SARS-CoV-2 neutralizing mAb clones that have single-digit nanomolar affinity and low-picomolar avidity, and generated a bispecific antibody. Lead antibodies showed strong inhibitory activity against historical SARS-CoV-2 and several emerging variants of concern. We solved several cryo-EM structures at ~3 Angstrom resolution of these neutralizing antibodies in complex with prefusion spike trimer ectodomain, and revealed distinct epitopes, binding patterns, and conformations. The lead clones also showed potent efficacy in vivo against authentic SARS-CoV-2 in both prophylactic and therapeutic settings. We also generated and characterized a humanized antibody to facilitate translation and drug development. The humanized clone also has strong potency against both the original virus and the B.1.617.2 Delta variant. These mAbs expand the repertoire of therapeutics against SARS-CoV-2 and emerging variants.

Single Cell Sequencing of Induced Pluripotent Stem Cell Derived Retinal Ganglion Cells (iPSC-RGC) Reveals Distinct Molecular Signatures and RGC Subtypes

We intend to identify marker genes with differential gene expression (DEG) and RGC subtypes in cultures of human-induced pluripotent stem cell (iPSC)-derived retinal ganglion cells. Single-cell sequencing was performed on mature and functional iPSC-RGCs at day 40 using Chromium Single Cell 3’ V3 protocols (10X Genomics). Sequencing libraries were run on Illumina Novaseq to generate 150 PE reads. Demultiplexed FASTQ files were mapped to the hg38 reference genome using the STAR package, and cluster analyses were performed using a cell ranger and BBrowser2 software. QC analysis was performed by removing the reads corresponding to ribosomal and mitochondrial genes, as well as cells that had less than 1X mean absolute deviation (MAD), resulting in 4705 cells that were used for further analyses. Cells were separated into clusters based on the gene expression normalization via PCA and TSNE analyses using the Seurat tool and/or Louvain clustering when using BBrowser2 software. DEG analysis identified subsets of RGCs with markers like MAP2, RBPMS, TUJ1, BRN3A, SOX4, TUBB3, SNCG, PAX6 and NRN1 in iPSC-RGCs. Differential expression analysis between separate clusters identified significant DEG transcripts associated with cell cycle, neuron regulatory networks, protein kinases, calcium signaling, growth factor hormones, and homeobox transcription factors. Further cluster refinement identified RGC diversity and subtype specification within iPSC-RGCs. DEGs can be used as biomarkers for RGC subtype classification, which will allow screening model systems that represent a spectrum of diseases with RGC pathology.

Dopamine and GPCR-mediated modulation of DN1 clock neurons gates the circadian timing of sleep

The metronome-like circadian regulation of sleep timing must still adapt to an uncertain environment. Recent studies in Drosophila indicate that neuromodulation not only plays a key role in clock neuron synchronization but also affects interactions between the clock network and brain sleep centers. We show here that the targets of neuromodulators, G-Protein Coupled Receptors (GPCRs), are highly enriched in the fly brain circadian clock network. Single cell sequencing indicates that they are not only differentially expressed but also define clock neuron identity. We generated a comprehensive guide library to mutagenize individual GPCRs in specific neurons and verified the strategy with a targeted sequencing approach. Combined with a behavioral screen, the mutagenesis strategy revealed a novel role of dopamine in sleep regulation by identifying two dopamine receptors and a clock neuron subpopulation that gate the timing of sleep.