Mechanisms of transcription regulation by CarD in Mycobacterium

Mycobacterium tuberculosis (Mtb) is an important human pathogen that is responsible for over 1 million deaths each year. As a bacterial pathogen, Mtb is highly adapted to survival within the host environment, which imposes numerous environmental stresses on the bacteria. To survive these challenges, Mtb utilizes a network of transcription factors to adapt its gene expression and physiology. CarD is an essential transcription factor in mycobacteria that binds directly to RNA polymerase (RNAP) rather than DNA sequence motifs on the chromosome. Prior mechanistic studies of CarD’s function in mycobacteria have been limited to studies of CarD’s effects on individual kinetic rate constants in a handful of promoter contexts. However, chromatin-immunoprecipitation sequencing (ChIP-seq) studies indicate that CarD is present broadly across the mycobacterial genome. Therefore, to gain a holistic understanding of CarD’s role at all mycobacterial promoters, we performed RNA-sequencing (RNA-seq) on a set of Mtb and Mycobacterium smegmatis strains with point mutations causing defects in CarD’s function. Our study demonstrated that over 50% of the Mtb genome is transcriptionally responsive to CarD mutation and revealed a novel bi-functional role of CarD as both a transcriptional activator and a transcriptional repressor. I performed bioinformatic analyses to show that CarD-regulated promoters could not be defined by a specific DNA sequence motif but that the direction of regulation was correlated with promoter characteristics such as -10 element conservation and discriminator G+C%. Our RNA-seq dataset raised a new question – ‘How does CarD achieve regulatory specificity without binding specificity?’. In collaboration with the Galburt Lab, we developed a model in which the direction of CarD regulation is dictated by a promoter’s basal transcription initiation kinetics rather than transcription factor binding. Specifically, our model predicts that CarD would activate transcription from promoters that form an unstable promoter open complex (RPo) and repress transcription from promoters that form a stable RPo by inhibiting the step of promoter escape. To test this model, I performed in vitro transcription studies to determine CarD’s direct regulatory effect on a panel of promoters with varying levels of basal RPo stability. I showed that, indeed, while CarD activated transcription from the wild-type ribosomal RNA promoter Mtb rrnAP3, CarD repressed transcription from more stable promoter contexts. Furthermore, I showed that RPo stability and CarD regulation could be influenced by sequence-independent factors such as DNA supercoiling, revealing another dynamic of transcription regulation. Using the wealth of transcriptomic data that I gathered, I examined the overlap between CarD’s in vivo regulon with other known regulons to gain insight into CarD’s role in mycobacterial physiology. Although I could not identify any specific downstream transcriptional pathway that was uniformly differentially expressed, CarD’s regulon overlapped with numerous stress-responsive regulons including the DosRST two-component system and the alternative sigma factors σF, σH, and σM. My thesis work advances our understanding of how RNAP-binding bacterial transcription factors like CarD are capable of enacting specific transcriptional responses over a broad regulon. My research also highlights how a single transcription factor can exert multiple functions under different contexts including contexts that cannot be understood from DNA sequence alone. Lastly, my work on CarD may help inform future design of Mtb therapeutics by deepening our understanding of the transcriptional programs that Mtb uses to endure environmental stresses

MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

The recent GPT-4 has demonstrated extraordinary multi-modal abilities, such as directly generating websites from handwritten text and identifying humorous elements within images. These features are rarely observed in previous vision-language models. We believe the primary reason for GPT-4's advanced multi-modal generation capabilities lies in the utilization of a more advanced large language model (LLM). To examine this phenomenon, we present MiniGPT-4, which aligns a frozen visual encoder with a frozen LLM, Vicuna, using just one projection layer. Our findings reveal that MiniGPT-4 possesses many capabilities similar to those exhibited by GPT-4 like detailed image description generation and website creation from hand-written drafts. Furthermore, we also observe other emerging capabilities in MiniGPT-4, including writing stories and poems inspired by given images, providing solutions to problems shown in images, teaching users how to cook based on food photos, etc. In our experiment, we found that only performing the pretraining on raw image-text pairs could produce unnatural language outputs that lack coherency including repetition and fragmented sentences. To address this problem, we curate a high-quality, well-aligned dataset in the second stage to finetune our model using a conversational template. This step proved crucial for augmenting the model's generation reliability and overall usability. Notably, our model is highly computationally efficient, as we only train a projection layer utilizing approximately 5 million aligned image-text pairs. Our code, pre-trained model, and collected dataset are available at https://minigpt-4.github.io/.Comment: Project Website: https://minigpt-4.github.io/; Code, Pretrained Model, and Dataset: https://github.com/Vision-CAIR/MiniGPT-4; Deyao Zhu and Jun Chen contributed equally to this wor

Study on microstructure mechanism of sandstone based on complex network theory

Rock contains a large number of micro-pores, which are of different shapes and complex structures. The structure information of sandstones is extracted based on different porosities through X-ray CT (Computer Tomography) scanning, photo processing techniques and complex network method to explore the topological structure of sandstone seepage network. The results show that sandstone seepage network has scale-free property. The minute quantities of pores with more throat connections have vital functions of overall connectivity of sandstone seepage network, while sandstone seepage network has strong robustness with random error. This research can provide reference for across scales research of porous seepage and multi-disciplinary application of complex network theory

Cold atmospheric plasma for selectively ablating metastatic breast cancer cells

Traditional breast cancer treatments such as surgery and radiotherapy contain many inherent limitations with regards to incomplete and nonselective tumor ablation. Cold atomospheric plasma (CAP) is an ionized gas where the ion temperature is close to room temperature. It contains electrons, charged particles, radicals, various excited molecules, UV photons and transient electric fields. These various compositional elements have the potential to either enhance and promote cellular activity, or disrupt and destroy them. In particular, based on this unique composition, CAP could offer a minimally-invasive surgical approach allowing for specific cancer cell or tumor tissue removal without influencing healthy cells. Thus, the objective of this research is to investigate a novel CAP-based therapy for selectively bone metastatic breast cancer treatment. For this purpose, human metastatic breast cancer (BrCa) cells and bone marrow derived human mesenchymal stem cells (MSCs) were separately treated with CAP, and behavioral changes were evaluated after 1, 3, and 5 days of culture. With different treatment times, different BrCa and MSC cell responses were observed. Our results showed that BrCa cells were more sensitive to these CAP treatments than MSCs under plasma dose conditions tested. It demonstrated that CAP can selectively ablate metastatic BrCa cells in vitro without damaging healthy MSCs at the metastatic bone site. In addition, our study showed that CAP treatment can significantly inhibit the migration and invasion of BrCa cells. The results suggest the great potential of CAP for breast cancer therapy

SOAP3-dp: Fast, Accurate and Sensitive GPU-based Short Read Aligner

To tackle the exponentially increasing throughput of Next-Generation Sequencing (NGS), most of the existing short-read aligners can be configured to favor speed in trade of accuracy and sensitivity. SOAP3-dp, through leveraging the computational power of both CPU and GPU with optimized algorithms, delivers high speed and sensitivity simultaneously. Compared with widely adopted aligners including BWA, Bowtie2, SeqAlto, GEM and GPU-based aligners including BarraCUDA and CUSHAW, SOAP3-dp is two to tens of times faster, while maintaining the highest sensitivity and lowest false discovery rate (FDR) on Illumina reads with different lengths. Transcending its predecessor SOAP3, which does not allow gapped alignment, SOAP3-dp by default tolerates alignment similarity as low as 60 percent. Real data evaluation using human genome demonstrates SOAP3-dp's power to enable more authentic variants and longer Indels to be discovered. Fosmid sequencing shows a 9.1 percent FDR on newly discovered deletions. SOAP3-dp natively supports BAM file format and provides a scoring scheme same as BWA, which enables it to be integrated into existing analysis pipelines. SOAP3-dp has been deployed on Amazon-EC2, NIH-Biowulf and Tianhe-1A.Comment: 21 pages, 6 figures, submitted to PLoS ONE, additional files available at "https://www.dropbox.com/sh/bhclhxpoiubh371/O5CO_CkXQE". Comments most welcom