Optimising mRNA vaccines manufacturing by using Machine learning approaches

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Maximizing mRNA vaccine production with Bayesian optimization

Messenger RNA (mRNA) vaccines are a new alternative to conventional vaccines with a prominent role in infectious disease control. These vaccines are produced in in vitro transcription (IVT) reactions, catalyzed by RNA polymerase in cascade reactions. To ensure an efficient and cost-effective manufacturing process, essential for a large-scale production and effective vaccine supply chain, the IVT reaction needs to be optimized. IVT is a complex reaction that contains a large number of variables that can affect its outcome. Traditional optimization methods rely on classic Design of Experiments methods, which are time-consuming and can present human bias or based on simplified assumptions. In this contribution, we propose the use of Machine Learning approaches to perform a data-driven optimization of an mRNA IVT reaction. A Bayesian optimization method and model interpretability techniques were used to automate experiment design, providing a feedback loop. IVT reaction conditions were found under 60 optimization runs that produced 12 g · L−1 in solely 2 h. The results obtained outperform published industry standards and data reported in literature in terms of both achievable reaction yield and reduction of production time. Furthermore, this shows the potential of Bayesian optimization as a cost-effective optimization tool within (bio)chemical applications

Protein-DNA interactions define the mechanistic aspects of circle formation and insertion reactions in IS2 transposition

<p>Abstract</p> <p>Background</p> <p>Transposition in IS<it>3</it>, IS<it>30</it>, IS<it>21 </it>and IS<it>256 </it>insertion sequence (IS) families utilizes an unconventional two-step pathway. A figure-of-eight intermediate in Step I, from asymmetric single-strand cleavage and joining reactions, is converted into a double-stranded minicircle whose junction (the abutted left and right ends) is the substrate for symmetrical transesterification attacks on target DNA in Step II, suggesting intrinsically different synaptic complexes (SC) for each step. Transposases of these ISs bind poorly to cognate DNA and comparative biophysical analyses of SC I and SC II have proven elusive. We have prepared a native, soluble, active, GFP-tagged fusion derivative of the IS<it>2 </it>transposase that creates fully formed complexes with single-end and minicircle junction (MCJ) substrates and used these successfully in hydroxyl radical footprinting experiments.</p> <p>Results</p> <p>In IS2, Step I reactions are physically and chemically asymmetric; the left imperfect, inverted repeat (IRL), the exclusive recipient end, lacks donor function. In SC I, different protection patterns of the cleavage domains (CDs) of the right imperfect inverted repeat (IRR; extensive <it>in cis</it>) and IRL (selective <it>in trans</it>) at the single active cognate IRR catalytic center (CC) are related to their donor and recipient functions. In SC II, extensive binding of the IRL CD <it>in trans </it>and of the abutted IRR CD <it>in cis </it>at this CC represents the first phase of the complex. An MCJ substrate precleaved at the 3' end of IRR revealed a temporary transition state with the IRL CD disengaged from the protein. We propose that in SC II, sequential 3' cleavages at the bound abutted CDs trigger a conformational change, allowing the IRL CD to complex to its cognate CC, producing the second phase. Corroborating data from enhanced residues and curvature propensity plots suggest that CD to CD interactions in SC I and SC II require IRL to assume a bent structure, to facilitate binding <it>in trans</it>.</p> <p>Conclusions</p> <p>Different transpososomes are assembled in each step of the IS<it>2 </it>transposition pathway. Recipient versus donor end functions of the IRL CD in SC I and SC II and the conformational change in SC II that produces the phase needed for symmetrical IRL and IRR donor attacks on target DNA highlight the differences.</p

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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