Origin of the nuclear proteome on the basis of pre-existing nuclear localization signals in prokaryotic proteins

Evolutionary trajectory for nuclear functions of ciliary transport complex proteins

SUMMARYCilia and the nucleus were two defining features of the last eukaryotic common ancestor. In early eukaryotic evolution, these structures evolved through the diversification of a common membrane-coating ancestor, the protocoatomer. While in cilia, the descendants of this protein complex evolved into parts of the intraflagellar transport complexes and BBSome, the nucleus gained its selectivity by recruiting protocoatomer-like proteins to the nuclear envelope to form the selective nuclear pore complexes. Recent studies show a growing number of proteins shared between the proteomes of the respective organelles, and it is currently unknown how ciliary transport proteins could acquire nuclear functions and vice versa. The nuclear functions of ciliary proteins are still observable today and remain relevant for the understanding of the disease mechanisms behind ciliopathies. In this work, we review the evolutionary history of cilia and nucleus and their respective defining proteins and integrate current knowledge into theories for early eukaryotic evolution. We postulate a scenario where both compartments co-evolved and that fits current models of eukaryotic evolution, explaining how ciliary proteins and nucleoporins acquired their dual functions.

Research progress in nucleus-targeted tumor therapy

The nucleus is considered the most important organelle in the cell as it plays a central role in controlling cell reproduction, metabolism, and the cell cycle. The successful delivery of drugs into the nucleus can achieve excellent therapeutic effects, which reveals the potential of nucleus-targeted therapy in precision medicine. However, the transportation of therapeutics into the nucleus remains a significant challenge due to various biological barriers. Herein, we summarize the recent progress in the nucleus-targeted drug delivery system (NDDS). The structures of the nucleus and nuclear envelope are first described in order to understand the mechanisms by which drugs cross the nuclear envelope. Then, various drug delivery strategies based on the mechanisms and their applications are discussed. Finally, the challenges and solutions in the field of nucleus-targeted drug delivery are raised for developing a more efficient NDDS and promoting its clinical transformation.

Improved datasets and evaluation methods for the automatic prediction of DNA-binding proteins

MOTIVATION

Accurate automatic annotation of protein function relies on both innovative models and robust datasets. Due to their importance in biological processes, the identification of DNA-binding proteins directly from protein sequence has been the focus of many studies. However, the datasets used to train and evaluate these methods have suffered from substantial flaws. We describe some of the weaknesses of the datasets used in previous DNA-binding protein literature and provide several new datasets addressing these problems. We suggest new evaluative benchmark tasks that more realistically assess real-world performance for protein annotation models. We propose a simple new model for the prediction of DNA-binding proteins and compare its performance on the improved datasets to two previously published models. In addition, we provide extensive tests showing how the best models predict across taxa.

RESULTS

Our new gradient boosting model, which uses features derived from a published protein language model, outperforms the earlier models. Perhaps surprisingly, so does a baseline nearest neighbor model using BLAST percent identity. We evaluate the sensitivity of these models to perturbations of DNA-binding regions and control regions of protein sequences. The successful data-driven models learn to focus on DNA-binding regions. When predicting across taxa, the best models are highly accurate across species in the same kingdom and can provide some information when predicting across kingdoms.

AVAILABILITY AND IMPLEMENTATION

The data and results for this article can be found at https://doi.org/10.5281/zenodo.5153906. The code for this article can be found at https://doi.org/10.5281/zenodo.5153683. The code, data and results can also be found at https://github.com/AZaitzeff/tools_for_dna_binding_proteins.

Global mapping of cancers: The Cancer Genome Atlas and beyond

Cancer genomes have been explored from the early 2000s through massive exome sequencing efforts, leading to the publication of The Cancer Genome Atlas in 2013. Sequencing techniques have been developed alongside this project and have allowed scientists to bypass the limitation of costs for whole-genome sequencing (WGS) of single specimens by developing more accurate and extensive cancer sequencing projects, such as deep sequencing of whole genomes and transcriptomic analysis. The Pan-Cancer Analysis of Whole Genomes recently published WGS data from more than 2600 human cancers together with almost 1200 related transcriptomes. The application of WGS on a large database allowed, for the first time in history, a global analysis of features such as molecular signatures, large structural variations and noncoding regions of the genome, as well as the evaluation of RNA alterations in the absence of underlying DNA mutations. The vast amount of data generated still needs to be thoroughly deciphered, and the advent of machine-learning approaches will be the next step towards the generation of personalized approaches for cancer medicine. The present manuscript wants to give a broad perspective on some of the biological evidence derived from the largest sequencing attempts on human cancers so far, discussing advantages and limitations of this approach and its power in the era of machine learning.

Molecular coevolution of nuclear and nucleolar localization signals inside basic domain of HIV-1 Tat

During evolution, viruses had to adapt to an increasingly complex environment of eukaryotic cells. Viral proteins that need to enter the cell nucleus or associate with nucleoli possess nuclear localization signals (NLSs) and nucleolar localization signals (NoLSs) for nuclear and nucleolar accumulation, respectively. As viral proteins are relatively small, acquisition of novel sequences seems to be a more complicated task for viruses than for eukaryotes. Here, we carried out a comprehensive analysis of the basic domain (BD) of HIV-1 Tat to show how viral proteins might evolve with NLSs and NoLSs without an increase in protein size. The HIV-1 Tat BD is involved in several functions, the most important being the transactivation of viral transcription. The BD also functions as an NLS, although it is substantially longer than a typical NLS. It seems that different regions in the BD could function as NLSs due to its enrichment with positively charged amino acids. Additionally, the high positive net charge inevitably causes the BD to function as an NoLS through a charge-specific mechanism. The integration of NLSs and NoLSs into functional domains enriched with positively charged amino acids might be a mechanism that allows the condensation of different functional sequences in small protein regions and, as a result, to reduce protein size, influencing the origin and evolution of NLSs and NoLSs in viruses. IMPORTANCE Here, we investigated the molecular mechanism of NLS and NoLS integration into the basic domain of HIV-1 Tat (⁴⁹RKKRRQRRR⁵⁷), and found that these two supplementary functions (i.e., function of NLS and NoLS) are embedded in the basic domain amino acid sequence. The integration of NLSs and NoLSs into functional domains of viral proteins enriched with positively charged amino acids is a mechanism that allows the concentration of different functions within small protein regions. Integration of NLS and NoLS into functional protein domains might have influenced the viral evolution, as this could prevent an increase in the protein size.