Biology subjects

Berezin, C.-T.

Publications and source records attributed to Berezin, C.-T..

6 recordsLinked to original sources

bioRxiv2025

Bigger Is Better Than Many: A Strategy to Optimize Multi-Gene Co-Expression

Large plasmids are often avoided in mammalian co-transfection due to the assumption that they transfect poorly, driving the use of multiple smaller plasmids. Here, we pair finite-state-projection modeling with flow cytometry experiments to compare one-, two-, and three-plasmid delivery of GFP/BFP/RFP. Estimated entry rates were size-independent from 4.9 to 16.4 kb, indicating that plasmid length is not the dominant barrier in this range. Our results suggest that using lipofectamine slightly increases co-transfection efficiency due to the ability of lipoplexes to contain multiple plasmids. However, this benefit is limited to only delivering two plasmids. Additionally, we show that contrary to current beliefs, putting all genes onto the same plasmid both increases the probability that a cell will express all genes of interest and results in a tighter correlation of gene expression levels compared to these multi-plasmid systems. Together, these results identify multi-cargo delivery and not plasmid size as the key constraint on co-transfection and show that single-plasmid designs are generally preferable for applications such as viral-vector production. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/675629v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@251928org.highwire.dtl.DTLVardef@196d1cborg.highwire.dtl.DTLVardef@a781e9org.highwire.dtl.DTLVardef@1420928_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

The Transcriptional Gradient in Negative-Strand RNA Viruses Suggests a Common RNA Transcription Mechanism

We introduce a novel model of nonsegmented negative-strand RNA virus (NNSV) transcription. Previous models have relied on polymerase behavioral differences in the highly conserved intergenic sequences. Our model hypothesizes the transcriptional gradient in NNSVs is explained through a simple model with two parameters associated with the viral polymerase. Most differences in expression can be attributed to the processivity of the polymerase while additional attenuation occurs in the presence of overlapping genes. This model reveals a correlation between polymerase processivity and genome length, which is consistent with the universal entry of polymerases through the 3 end of the genome. Using this model, it is now possible to predict the transcriptional behavior of NNSVs from genotype alone, revolutionizing the design of novel NNSV variants for biomedical applications.

bioinformatics↗

bioRxiv2024

Self-Documenting Plasmids

SO_SCPLOWUMMARYC_SCPLOWPlasmids are the workhorse of biotechnology. These small DNA molecules are used to produce recombinant proteins and to engineer living organisms. They can be regarded as the blueprints of many biotechnology products. It is, therefore, critical to ensure that the sequences of these DNA molecules match their intended designs. Yet, plasmid verification remains challenging. To secure the exchange of plasmids in research and development workflows, we have developed self-documenting plasmids that encode information about themselves in their own DNA molecules. Users of self-documenting plasmids can retrieve critical information about the plasmid without prior knowledge of the plasmid identity. The insertion of documentation in the plasmid sequence does not adversely affect their propagation in bacteria and does not compromise protein expression in mammalian cells. This technology simplifies plasmid verification, hardens supply chains, and has the potential to transform the protection of intellectual property in the life sciences.

synthetic biology↗

bioRxiv2024

Hybrid Sequencing Facilitates Robust De Novo Plasmid Assembly

Despite the wide use of plasmids in research and clinical production, the need to verify plasmid sequences is a bottleneck that is too often underestimated in the manufacturing process. Although sequencing platforms continue to improve, the method and assembly pipeline chosen still influence the final plasmid assembly sequence. Furthermore, few dedicated tools exist for plasmid assembly, especially for de novo assembly. Here, we evaluated short-read, long-read, and hybrid (both short and long reads) de novo assembly pipelines across three replicates of a 24-plasmid library. Consistent with previous characterizations of each sequencing technology, short-read assemblies had issues resolving GC-rich regions, and long-read assemblies commonly had small insertions and deletions, especially in repetitive regions. The hybrid approach facilitated the most accurate, consistent assembly generation and identified mutations relative to the reference sequence. Although Sanger sequencing can be used to verify specific regions, some GC-rich and repetitive regions were difficult to resolve using any method, suggesting that easily sequenced genetic parts should be prioritized in the design of new genetic constructs. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/586694v2_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@13945c1org.highwire.dtl.DTLVardef@11287a8org.highwire.dtl.DTLVardef@1885654org.highwire.dtl.DTLVardef@1dbdbf3_HPS_FORMAT_FIGEXP M_FIG GRAPHICAL ABSTRACT C_FIG

synthetic biology↗

bioRxiv2023

Dopamine enhances GABAA receptor-mediated current amplitude in a subset of intrinsically photosensitive retinal ganglion cells

Neuromodulation in the retina is crucial for effective processing of retinal signal at different levels of illuminance. Intrinsically photosensitive retinal ganglion cells (ipRGCs), the neurons that drive non-image forming visual functions, express a variety of neuromodulatory receptors that tune intrinsic excitability as well as synaptic inputs. Past research has examined actions of neuromodulators on light responsiveness of ipRGCs, but less is known about how neuromodulation affects synaptic currents in ipRGCs. To better understand how neuromodulators affect synaptic processing in ipRGC, we examine actions of opioid and dopamine agonists have on inhibitory synaptic currents in ipRGCs. Although {micro}-opioid receptor (MOR) activation had no effect on {gamma}-aminobutyric acid (GABA) currents, dopamine (via the D1R) amplified GABAergic currents in a subset of ipRGCs. Furthermore, this D1R-mediated facilitation of the GABA conductance in ipRGCs was mediated by a cAMP/PKA-dependent mechanism. Taken together, these findings reinforce the idea that dopamines modulatory role in retinal adaptation affects both non-image forming as well as image forming visual functions.

neuroscience↗

bioRxiv2023

Stochastic model of vesicular stomatitis virus replication reveals mutational effects on virion production

We present the first complete stochastic model of vesicular stomatitis virus (VSV) intracellular replication. Previous models developed to capture VSVs intracellular replication have either been ODE-based or have not represented the complete replicative cycle, limiting our ability to understand the impact of the stochastic nature of early cellular infections on virion production between cells and how these dynamics change in response to mutations. Our model accurately predicts changes in mean virion production in gene-shuffled VSV variants and can capture the distribution of the number of viruses produced. This model has allowed us to enhance our understanding of intercellular variability in virion production, which appears to be influenced by the duration of the early phase of infection, and variation between variants, arising from balancing the time the genome spends in the active state, the speed of incorporating new genomes into virions, and the production of viral components. Being a stochastic model, we can also assess other effects of mutations beyond just the mean number of virions produced, including the probability of aborted infections and the standard deviation of the number of virions produced. Our model provides a biologically interpretable framework for studying the stochastic nature of VSV replication, shedding light on the mechanisms underlying variation in virion production. In the future, this model could enable the design of more complex viral phenotypes when attenuating VSV, moving beyond solely considering the mean number of virions produced. Author SummaryThis study presents the first complete stochastic model of vesicular stomatitis virus (VSV) replication. Our model captures the dynamic process of VSVs replication within host cells, accounting for the stochastic nature of early cellular infections and how these dynamics change in response to mutations. By accurately predicting changes in mean virion production and the distribution of viruses in gene-shuffled VSV variants, our model enhances our understanding of viral replication and the variation we see in virion production. Importantly, our findings shed light on the mechanisms underlying the production of VSV virions, revealing the influence of factors such as the duration of the early infection phase and the interplay between the genomes ability to switch into an inactive state and viral protein production. We go beyond assessing the mean number of virions produced and examine other effects of mutations, including the probability of aborted infections and the variability in virion production. This stochastic model provides a valuable framework for studying the complex nature of viral replication, contributing to our understanding of single-cell viral dynamics and variability. Ultimately, this knowledge could pave the way for designing more effective strategies to attenuate VSV.

systems biology↗