Occupancy classification of position weight matrix-inferred transcription factor binding sites

PWM2Vec: An Efficient Embedding Approach for Viral Host Specification from Coronavirus Spike Sequences

The study of host specificity has important connections to the question about the origin of SARS-CoV-2 in humans which led to the COVID-19 pandemic-an important open question. There are speculations that bats are a possible origin. Likewise, there are many closely related (corona)viruses, such as SARS, which was found to be transmitted through civets. The study of the different hosts which can be potential carriers and transmitters of deadly viruses to humans is crucial to understanding, mitigating, and preventing current and future pandemics. In coronaviruses, the surface (S) protein, or spike protein, is important in determining host specificity, since it is the point of contact between the virus and the host cell membrane. In this paper, we classify the hosts of over five thousand coronaviruses from their spike protein sequences, segregating them into clusters of distinct hosts among birds, bats, camels, swine, humans, and weasels, to name a few. We propose a feature embedding based on the well-known position weight matrix (PWM), which we call PWM2Vec, and we use it to generate feature vectors from the spike protein sequences of these coronaviruses. While our embedding is inspired by the success of PWMs in biological applications, such as determining protein function and identifying transcription factor binding sites, we are the first (to the best of our knowledge) to use PWMs from viral sequences to generate fixed-length feature vector representations, and use them in the context of host classification. The results on real world data show that when using PWM2Vec, machine learning classifiers are able to perform comparably to the baseline models in terms of predictive performance and runtime-in some cases, the performance is better. We also measure the importance of different amino acids using information gain to show the amino acids which are important for predicting the host of a given coronavirus. Finally, we perform some statistical analyses on these results to show that our embedding is more compact than the embeddings of the baseline models.

A system biology approach to identify regulatory pathways underlying the neuroendocrine control of female puberty in rats and nonhuman primates

This article is part of a Special Issue "Puberty and Adolescence". Puberty is a major developmental milestone controlled by the interaction of genetic factors and environmental cues of mostly metabolic and circadian nature. An increased pulsatile release of the decapeptide gonadotropin releasing hormone (GnRH) from hypothalamic neurosecretory neurons is required for both the initiation and progression of the pubertal process. This increase is brought about by coordinated changes that occur in neuronal and glial networks associated with GnRH neurons. These changes ultimately result in increased neuronal and glial stimulatory inputs to the GnRH neuronal network and a reduction of transsynaptic inhibitory influences. While some of the major players controlling pubertal GnRH secretion have been identified using gene-centric approaches, much less is known about the system-wide control of the overall process. Because the pubertal activation of GnRH release involves a diversity of cellular phenotypes, and a myriad of intracellular and cell-to-cell signaling molecules, it appears that the overall process is controlled by a highly coordinated and interactive regulatory system involving hundreds, if not thousands, of gene products. In this article we will discuss emerging evidence suggesting that these genes are arranged as functionally connected networks organized, both internally and across sub-networks, in a hierarchical fashion. According to this concept, the core of these networks is composed of transcriptional regulators that, by directing expression of downstream subordinate genes, provide both stability and coordination to the cellular networks involved in initiating the pubertal process. The integrative response of these gene networks to external inputs is postulated to be coordinated by epigenetic mechanisms.