Long non-coding RNAs (lncRNAs) have received attention in recent years for their regulatory roles in diverse biological contexts including cancer, yet large gaps remain in our understanding of their ...mechanisms and global maps of their targets. In this work, we investigated a basic unanswered question of lncRNA systems biology: to what extent can gene expression variation across individuals be attributed to lncRNA-driven regulation? To answer this, we analyzed RNA-seq data from a cohort of breast cancer patients, explaining each gene’s expression variation using a small set of automatically selected lncRNA regulators. A key aspect of this analysis is that it accounts for confounding effects of transcription factors (TFs) as common regulators of a lncRNA-mRNA pair, to enrich the explained gene expression for lncRNA-mediated regulation. We found that for 16% of analyzed genes, lncRNAs can explain more than 20% of expression variation. We observed 25–50% of the putative regulator lncRNAs to be in ‘cis’ to, i.e., overlapping or located proximally to the target gene. This led us to quantify the global regulatory impact of such cis-located lncRNAs, which was found to be substantially greater than that of trans-located lncRNAs. Additionally, by including statistical interaction terms involving lncRNA-protein pairs as predictors in our regression models, we identified cases where a lncRNA’s regulatory effect depends on the presence of a TF or RNA-binding protein. Finally, we created a high-confidence lncRNA-gene regulatory network whose edges are supported by co-expression as well as a plausible mechanism such as cis-action, protein scaffolding or competing endogenous RNAs. Our work is a first attempt to quantify the extent of gene expression control exerted globally by lncRNAs, especially those located proximally to their regulatory targets, in a specific biological (breast cancer) context. It also marks a first step towards systematic reconstruction of lncRNA regulatory networks, going beyond the current paradigm of co-expression networks, and motivates future analyses assessing the generalizability of our findings to additional biological contexts.
This paper reviews the state of emerging transistor technologies capable of terahertz amplification, as well as the state of transistor modeling as required in terahertz electronic circuit research. ...Commercial terahertz radar sensors of today are being built using bulky and expensive technologies such as Schottky diode detectors and lasers, as well as using some emerging detection methods. Meanwhile, a considerable amount of research effort has recently been invested in process development and modeling of transistor technologies capable of amplifying in the terahertz band. Indium phosphide (InP) transistors have been able to reach maximum oscillation frequency (
) values of over 1 THz for around a decade already, while silicon-germanium bipolar complementary metal-oxide semiconductor (BiCMOS) compatible heterojunction bipolar transistors have only recently crossed the
= 0.7 THz mark. While it seems that the InP technology could be the ultimate terahertz technology, according to the
and related metrics, the BiCMOS technology has the added advantage of lower cost and supporting a wider set of integrated component types. BiCMOS can thus be seen as an enabling factor for re-engineering of complete terahertz radar systems, for the first time fabricated as miniaturized monolithic integrated circuits. Rapid commercial deployment of monolithic terahertz radar chips, furthermore, depends on the accuracy of transistor modeling at these frequencies. Considerations such as fabrication and modeling of passives and antennas, as well as packaging of complete systems, are closely related to the two main contributions of this paper and are also reviewed here. Finally, this paper probes active terahertz circuits that have already been reported and that have the potential to be deployed in a re-engineered terahertz radar sensor system and attempts to predict future directions in re-engineering of monolithic radar sensors.
Many long non-coding RNAs, known to be involved in transcriptional regulation, are enriched in the nucleus and interact with chromatin. However, their mechanisms of chromatin interaction and the ...served cellular functions are poorly understood. We sought to characterize the mechanisms of lncRNA nuclear retention by systematically mapping the sequence and chromatin features that distinguish lncRNA-interacting genomic segments.
We found DNA 5-mer frequencies to be predictive of chromatin interactions for all lncRNAs, suggesting sequence-specificity as a global theme in the interactome. Sequence features representing protein-DNA and protein-RNA binding motifs revealed potential mechanisms for specific lncRNAs. Complementary to these global themes, transcription-related features and DNA-RNA triplex formation potential were noted to be highly predictive for two mutually exclusive sets of lncRNAs. DNA methylation was also noted to be a significant predictor, but only when combined with other epigenomic features.
Taken together, our statistical findings suggest that a group of lncRNAs interacts with transcriptionally inactive chromatin through triplex formation, whereas another group interacts with transcriptionally active regions and is involved in DNA Damage Response (DDR) through formation of R-loops. Curiously, we observed a strong pattern of enrichment of 5-mers in four potentially interacting entities: lncRNA-bound DNA tiles, lncRNAs, miRNA seed sequences, and repeat elements. This finding points to a broad sequence-based network of interactions that may underlie regulation of fundamental cellular functions. Overall, this study reveals diverse sequence and chromatin features related to lncRNA-chromatin interactions, suggesting potential mechanisms of nuclear retention and regulatory function.
Large-scale data acquisition and analysis are often required in the successful implementation of the design, build, test, and learn (DBTL) cycle in biosystems design. However, it has long been ...hindered by experimental cost, variability, biases, and missed insights from traditional analysis methods. Here, we report the application of an integrated robotic system coupled with machine learning algorithms to fully automate the DBTL process for biosystems design. As proof of concept, we have demonstrated its capacity by optimizing the lycopene biosynthetic pathway. This fully-automated robotic platform, BioAutomata, evaluates less than 1% of possible variants while outperforming random screening by 77%. A paired predictive model and Bayesian algorithm select experiments which are performed by Illinois Biological Foundry for Advanced Biomanufacturing (iBioFAB). BioAutomata excels with black-box optimization problems, where experiments are expensive and noisy and the success of the experiment is not dependent on extensive prior knowledge of biological mechanisms.
The Public Health Emergency of International Concern declared the widespread outbreak of SARS-CoV-2 as a global pandemic emergency, which has resulted in 1,773,086 confirmed cases including 111,652 ...human deaths, as on 13 April 2020, as reported to World Health Organization. As of now, there are no vaccines or antiviral drugs declared to be officially useful against the infection. Saikosaponin is a group of oleanane derivatives reported in Chinese medicinal plants and are described for their anti-viral, anti-tumor, anti-inflammatory, anticonvulsant, antinephritis and hepatoprotective activities. They have also been known to have anti-coronaviral property by interfering the early stage of viral replication including absorption and penetration of the virus. Thus, the present study was undertaken to screen and evaluate the potency of different Saikosaponins against different sets of SARS-CoV-2 binding protein via computational molecular docking simulations. Docking was carried out on a Glide module of Schrodinger Maestro 2018-1 MM Share Version on NSP15 (PDB ID: 6W01) and Prefusion 2019-nCoV spike glycoprotein (PDB ID: 6VSB) from SARS-CoV-2. From the binding energy and interaction studies, the Saikosaponins U and V showed the best affinity towards both the proteins suggesting them to be future research molecule as they mark the desire interaction with NSP15, which is responsible for replication of RNA and also with 2019-nCoV spike glycoprotein which manage the connection with ACE2.
Communicated by Ramaswamy H. Sarma
Genomics is a Big Data science and is going to get much bigger, very soon, but it is not known whether the needs of genomics will exceed other Big Data domains. Projecting to the year 2025, we ...compared genomics with three other major generators of Big Data: astronomy, YouTube, and Twitter. Our estimates show that genomics is a "four-headed beast"--it is either on par with or the most demanding of the domains analyzed here in terms of data acquisition, storage, distribution, and analysis. We discuss aspects of new technologies that will need to be developed to rise up and meet the computational challenges that genomics poses for the near future. Now is the time for concerted, community-wide planning for the "genomical" challenges of the next decade.
Significance: The topic of the Fourth Industrial Revolution (4IR) became significant in South Africa from 2017, through advocacy, amongst others, by the University of Johannesburg and subsequently ...through the appointment of the Presidential Commission on 4IR. Preceding industrial revolutions each focused on a single technology: 4IR, however, speaks to a confluence of technologies and a synergy of computing, data, and communications technology, with artificial intelligence rapidly redefining the world of work. Conceptual and geopolitical challenges and potential negative societal implications notwithstanding, we argue that the 4IR paradigm shift is critical to South Africa and to realising the Sustainable Development Goals.
Intravital microscopy (IVM) emerged and matured as a powerful tool for elucidating pathways in biological processes. Although label-free multiphoton IVM is attractive for its non-perturbative nature, ...its wide application has been hindered, mostly due to the limited contrast of each imaging modality and the challenge to integrate them. Here we introduce simultaneous label-free autofluorescence-multiharmonic (SLAM) microscopy, a single-excitation source nonlinear imaging platform that uses a custom-designed excitation window at 1110 nm and shaped ultrafast pulses at 10 MHz to enable fast (2-orders-of-magnitude improvement), simultaneous, and efficient acquisition of autofluorescence (FAD and NADH) and second/third harmonic generation from a wide array of cellular and extracellular components (e.g., tumor cells, immune cells, vesicles, and vessels) in living tissue using only 14 mW for extended time-lapse investigations. Our work demonstrates the versatility and efficiency of SLAM microscopy for tracking cellular events in vivo, and is a major enabling advance in label-free IVM.
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