Biology subjects

Mauro, E.

Publications and source records attributed to Mauro, E..

3 recordsLinked to original sources

bioRxiv2022

Modulation of the functional interfaces between retroviral intasomes and the human nucleosome

Retroviral integration into cell chromatin requires the formation of integrase-viral DNA complexes, called intasomes, and their interaction with the target DNA wrapped around nucleosomes. To further study this mechanism we developed an alphaLISA approach using the prototype foamy virus (PFV) intasome and human nucleosome. This system allowed us to monitor the association between both partners and investigate the protein/protein and protein/DNA interactions engaged in the association with chromatin. Using this approach, we next screened the chemical OncoSET library and selected small molecules that could modulate the intasome/nucleosome complex. Molecules were selected as acting either on the DNA topology within the nucleosome or on the integrase/histone tail interactions. Within these compounds, doxorubicin and histone binders calixarenes were characterized using biochemical, structural and cellular approaches. These drugs were shown to inhibit PFV and HIV-1 integration in vitro as well as HIV-1 infection in primary PBMCs cells. Our work provides new information about intasome-nucleosome interaction determinants and paves the way for further unedited antiviral strategies that target the final step of intasome/chromatin anchoring.

microbiology↗

bioRxiv2021

ICOR: Improving codon optimization with recurrent neural networks

BackgroundIn protein sequences--as there are 61 sense codons but only 20 standard amino acids-- most amino acids are encoded by more than one codon. Although such synonymous codons do not alter the encoded amino acid sequence, their selection can dramatically affect the expression of the resulting protein. Codon optimization of synthetic DNA sequences is important for heterologous expression. However, existing solutions are primarily based on choosing high-frequency codons only, neglecting the important effects of rare codons. In this paper, we propose a novel recurrent-neural-network based codon optimization tool, ICOR, that aims to learn codon usage bias on a genomic dataset of Escherichia coli. We compile a dataset of over 7,000 non-redundant, high-expression, robust genes which are used for deep learning. The model uses a bidirectional long short-term memory-based architecture, allowing for the sequential context of codon usage in genes to be learned. Our tool can predict synonymous codons for synthetic genes toward optimal expression in Escherichia coli. ResultsWe demonstrate that sequential context achieved via RNN may yield codon selection that is more similar to the host genome. Based on computational metrics that predict protein expression, ICOR theoretically optimizes protein expression more than frequency-based approaches. ICOR is evaluated on 1,481 Escherichia coli genes as well as a benchmark set of 40 select DNA sequences whose heterologous expression has been previously characterized. ICORs performance is measured across five metrics: the Codon Adaptation Index, GC-content, negative repeat elements, negative cis-regulatory elements, and codon frequency distribution. ConclusionsThe results, based on in silico metrics, indicate that ICOR codon optimization is theoretically more effective in enhancing recombinant expression of proteins over other established codon optimization techniques. Our tool is provided as an open-source software package that includes the benchmark set of sequences used in this study.

synthetic biology↗

bioRxiv2020

Analysis of the intrinsic chromatin binding property of HIV-1 integrase and its regulation by LEDGF/p75 using human chromosomes spreads

Retroviral integration requires the stable insertion of the viral genome into the host chromosomes. During this process, the functional integration complex must associate with cellular chromatin via the interaction between retroviral integrase and nucleosomes. The final association between the HIV-1 integration complex and the nucleosomal target DNA remains unclear and may involve the chromatin-binding properties of both the retroviral integrase and its cellular cofactor LEDGF/p75. To date, there is no experimental system allowing the direct monitoring of this protein association with chromatin to depict the molecular mechanism of this process fully. To investigate this and understand the LEDGF/p75-mediated chromatin tethering of HIV-1 integrase further, we used both biochemical approaches and an unedited chromosome-binding assays. Our study revealed that retroviral IN has an intrinsic ability to bind and recognize specific chromatin regions even in the absence of its cofactor. We also showed that this integrase chromatin-binding property was modulated by the interaction with its cofactor LEDGF/p75, which redirected the enzyme to alternative chromatin regions. Using these approaches, we also better determined the chronology of efficient LEDGF/p75-mediated targeting of HIV-1 integrase to chromatin. In addition to supporting a chromatin-binding function of the integrase protein acting in concert with LEDGF/p75 for the optimal association with the nucleosomal substrate, our work precisely elucidates the mechanism of action of LEDGF/p75 in this crucial integration step.

microbiology↗