Biology subjects

Lau, A. K.

Publications and source records attributed to Lau, A. K..

4 recordsLinked to original sources

bioRxiv2021

High Throughput Fitness Profiling Reveals Loss Of GacS-GacA Regulation Improves Indigoidine Production In Pseudomonas putida

Pseudomonas putida KT2440 is an emerging industrial microbe amenable for use with renewable carbon streams including aromatics such as para-coumarate (pCA). We examined this microbe under common stirred-tank bioreactor parameters with quantitative fitness assays using a pooled transposon library containing nearly all (4,778) non-essential genes. Assessing differential fitness values by monitoring changes in mutant strain abundance over time identified 31 genes with improved fitness in multiple bioreactor-relevant parameters. Twenty-one genes from this subset were reconstructed, including GacA, a signaling protein, TtgB, an ABC transporter, and PP_0063, a lipid A acyltransferase. Twelve deletion strains with roles in varying cellular functions were evaluated for conversion of pCA, to a heterologous bioproduct, indigoidine. Several mutants, such as the {Delta}gacA strain improved both fitness in a bioreactor and showed an 8-fold improvement in indigoidine production (4.5 g/L, 0.29 g/g pCA, 23% MTY) from pCA as the carbon source.

systems biology↗

bioRxiv2020

Genome-scale metabolic rewiring to achieve predictable titers rates and yield of a non-native product at scale

Achieving high titer rates and yields (TRY) remains a bottleneck in the production of heterologous products through microbial systems, requiring elaborate engineering and many iterations. Reliable scaling of engineered strains is also rarely addressed in the first designs of the engineered strains. Both high TRY and scale are challenging metrics to achieve due to the inherent trade-off between cellular use of carbon towards growth vs. target metabolite production. We hypothesized that being able to strongly couple product formation with growth may lead to improvements across both metrics. In this study, we use elementary mode analysis to predict metabolic reactions that could be targeted to couple the production of indigoidine, a sustainable pigment, with the growth of the chosen host, Pseudomonas putida KT2440. We then filtered the set of 16 predicted reactions using -omics data. We implemented a total of 14 gene knockdowns using a CRISPRi method optimized for P. putida and show that the resulting engineered P. putida strain could achieve high TRY. The engineered pairing of product formation with carbon use also shifted production from stationary to exponential phase and the high TRY phenotype was maintained across scale. In one design cycle, we constructed an engineered P. putida strain that demonstrates close to 50% maximum theoretical yield (0.33 g indigoidine/g glucose consumed), reaching 25.6 g/L indigoidine and a rate of 0.22g/l/h in exponential phase. These desirable phenotypes were maintained from batch to fed-batch cultivation mode, and from 100ml shake flasks to 250 mL ambr(R) and 2 L bioreactors.

bioengineering↗

bioRxiv2019

Benchmarking of alignment-free sequence comparison methods

Alignment-free (AF) sequence comparison is attracting persistent interest driven by data-intensive applications. Hence, many AF procedures have been proposed in recent years, but a lack of a clearly defined benchmarking consensus hampers their performance assessment. Here, we present a community resource (http://afproject.org) to establish standards for comparing alignment-free approaches across different areas of sequence-based research. We characterize 74 AF methods available in 24 software tools for five research applications, namely, protein sequence classification, gene tree inference, regulatory element detection, genome-based phylogenetic inference and reconstruction of species trees under horizontal gene transfer and recombination events. The interactive web service allows researchers to explore the performance of alignment-free tools relevant to their data types and analytical goals. It also allows method developers to assess their own algorithms and compare them with current state-of-the-art tools, accelerating the development of new, more accurate AF solutions.

bioinformatics↗

bioRxiv2019

Read-SpaM: assembly-free and alignment-free comparison of bacterial genomes with low sequencing coverage

In many fields of biomedical research, it is important to estimate phylogenetic distances between taxa based on low-coverage sequencing reads. Major applications are, for example, phylogeny reconstruction, species identification from small sequencing samples, or bacterial strain typing in medical diagnostics. Herein, we adapt our previously developed software program Filtered Spaced-Word Matches (FSWM) for alignment-free phylogeny reconstruction to work on unassembled reads; we call this implementation Read-SpaM. Test runs on simulated reads from bacterial genomes show that our approach can estimate phylogenetic distances with high accuracy, even for large evolutionary distances and for very low sequencing coverage. Contact: bmorgen@gwdg.de

bioinformatics↗