scholarly journals ‘TeeBot’: A High Throughput Robotic Fermentation and Sampling System

Fermentation ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. 205
Author(s):  
Nicholas van Holst Pellekaan ◽  
Michelle Walker ◽  
Tommaso Watson ◽  
Vladimir Jiranek
Keyword(s):  
High Throughput ◽  
Best Practice ◽  
Fermentation Performance ◽  
Sampling System ◽  
Traditional Methods ◽  
Liquid Handling ◽  
Sample Density ◽  
Major Bottleneck ◽  
Shake Flasks ◽  
Downstream Analysis

When fermentation research requires the comparison of many strains or conditions, the major bottleneck is a technical one. Microplate approaches are not able to produce representative fermentative performance due to their inability to truly operate anaerobically, whilst more traditional methods do not facilitate sample density sufficient to assess enough candidates to be considered even medium throughput. Two robotic platforms have been developed that address these technological shortfalls. Both are built on commercially available liquid handling platforms fitted with custom labware. Results are presented detailing fermentation performance as compared to current best practice, i.e., shake flasks fitted with airlocks and sideports. The ‘TeeBot’ is capable sampling from 96 or 384 fermentations in 100 mL or 30 mL volumes, respectively, with airlock sealing and minimal headspace. Sampling and downstream analysis are facilitated by automated liquid handling, use of 96-well sample plate format and temporary cryo-storage (<0 °C).

scholarly journals A fully automated pipeline for the dynamic at‐line morphology analysis of microscale Aspergillus cultivation

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Roman Jansen ◽  
Kira Küsters ◽  
Holger Morschett ◽  
Wolfgang Wiechert ◽  
Marco Oldiges
Keyword(s):  
Filamentous Fungi ◽  
High Throughput ◽  
Automated Image Analysis ◽  
Height Velocity ◽  
Pellet Size ◽  
Application Study ◽  
Liquid Handling ◽  
Morphology Analysis ◽  
Development And Utilization ◽  
Increasing Demand

Abstract Background Morphology, being one of the key factors influencing productivity of filamentous fungi, is of great interest during bioprocess development. With increasing demand of high-throughput phenotyping technologies for fungi due to the emergence of novel time-efficient genetic engineering technologies, workflows for automated liquid handling combined with high-throughput morphology analysis have to be developed. Results In this study, a protocol allowing for 48 parallel microbioreactor cultivations of Aspergillus carbonarius with non-invasive online signals of backscatter and dissolved oxygen was established. To handle the increased cultivation throughput, the utilized microbioreactor is integrated into a liquid handling platform. During cultivation of filamentous fungi, cell suspensions result in either viscous broths or form pellets with varying size throughout the process. Therefore, tailor-made liquid handling parameters such as aspiration/dispense height, velocity and mixing steps were optimized and validated. Development and utilization of a novel injection station enabled a workflow, where biomass samples are automatically transferred into a flow through chamber fixed under a light microscope. In combination with an automated image analysis concept, this enabled an automated morphology analysis pipeline. The workflow was tested in a first application study, where the projected biomass area was determined at two different cultivation temperatures and compared to the microbioreactor online signals. Conclusions A novel and robust workflow starting from microbioreactor cultivation, automated sample harvest and processing via liquid handling robots up to automated morphology analysis was developed. This protocol enables the determination of projected biomass areas for filamentous fungi in an automated and high-throughput manner. This measurement of morphology can be applied to describe overall pellet size distribution and heterogeneity.

scholarly journals Genetically encoded biosensors for lignocellulose valorization

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Guadalupe Alvarez-Gonzalez ◽  
Neil Dixon
Keyword(s):  
High Throughput ◽  
Critical Factor ◽  
Modern Society ◽  
Low Carbon ◽  
Design And Optimization ◽  
Oil Reserves ◽  
Cell Factories ◽  
Major Bottleneck ◽  
Fuels And Chemicals ◽  
Pathway Regulation

Abstract Modern society is hugely dependent on finite oil reserves for the supply of fuels and chemicals. Moving our dependence away from these unsustainable oil-based feedstocks to renewable ones is, therefore, a critical factor towards the development of a low carbon bioeconomy. Lignin derived from biomass feedstocks offers great potential as a renewable source of aromatic compounds if methods for its effective valorization can be developed. Synthetic biology and metabolic engineering offer the potential to synergistically enable the development of cell factories with novel biosynthetic routes to valuable chemicals from these sustainable sources. Pathway design and optimization is, however, a major bottleneck due to the lack of high-throughput methods capable of screening large libraries of genetic variants and the metabolic burden associated with bioproduction. Genetically encoded biosensors can provide a solution by transducing the target metabolite concentration into detectable signals to provide high-throughput phenotypic read-outs and allow dynamic pathway regulation. The development and application of biosensors in the discovery and engineering of efficient biocatalytic processes for the degradation, conversion, and valorization of lignin are paving the way towards a sustainable and economically viable biorefinery.

scholarly journals Best practices for variant calling in clinical sequencing

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Daniel C. Koboldt
Keyword(s):  
Best Practices ◽  
Single Molecule ◽  
Best Practice ◽  
Variant Calling ◽  
Clinical Samples ◽  
Clinical Genetic ◽  
Inherited Disorders ◽  
Clinical Sequencing ◽  
Sequencing Technologies ◽  
Downstream Analysis

Abstract Next-generation sequencing technologies have enabled a dramatic expansion of clinical genetic testing both for inherited conditions and diseases such as cancer. Accurate variant calling in NGS data is a critical step upon which virtually all downstream analysis and interpretation processes rely. Just as NGS technologies have evolved considerably over the past 10 years, so too have the software tools and approaches for detecting sequence variants in clinical samples. In this review, I discuss the current best practices for variant calling in clinical sequencing studies, with a particular emphasis on trio sequencing for inherited disorders and somatic mutation detection in cancer patients. I describe the relative strengths and weaknesses of panel, exome, and whole-genome sequencing for variant detection. Recommended tools and strategies for calling variants of different classes are also provided, along with guidance on variant review, validation, and benchmarking to ensure optimal performance. Although NGS technologies are continually evolving, and new capabilities (such as long-read single-molecule sequencing) are emerging, the “best practice” principles in this review should be relevant to clinical variant calling in the long term.

scholarly journals Automated Analytical Measurement Processes Using a Dual-Arm Robotic System

2019 ◽  
Vol 24 (3) ◽  
pp. 354-356
Author(s):  
Heidi Fleischer ◽  
Shalaka Joshi ◽  
Thomas Roddelkopf ◽  
Michael Klos ◽  
Kerstin Thurow
Keyword(s):  
High Throughput ◽  
High Content Screening ◽  
Automation System ◽  
Analytical Measurement ◽  
Flexible Robots ◽  
Liquid Handling ◽  
Human Operators ◽  
Dual Arm Robot ◽  
Dual Arm ◽  
Direct Sample

The demand for automation in the analytical laboratory is high. In contrast to well-automated bioscreening and high-throughput and high-content screening processes, analytical measurement procedures are complex in their structure and changing frequently. Not only do robotic units have to perform transportation or specific single tasks, but also flexible robots are needed to cover several tasks, including transportation and direct sample manipulation. Due to their human-like structure, dual-arm robots are predestined for analytical measurement processes. A new study published in the journal Energies presents a novel integration of electronic piston pipettes into an automation system using a dual-arm robot to perform liquid handling tasks similar to human operators. In this commentary, the main findings are highlighted and discussed.

A Novel High-Throughput FLIPR Tetra–Based Method for Capturing Highly Confluent Kinetic Data for Structure–Kinetic Relationship Guided Early Drug Discovery

2021 ◽  
pp. 247255522110006
Author(s):  
Puneet Khurana ◽  
Lisa McWilliams ◽  
Jonathan Wingfield ◽  
Derek Barratt ◽  
Bharath Srinivasan
Keyword(s):  
Parameter Estimation ◽  
Drug Discovery ◽  
High Throughput ◽  
Kinetic Data ◽  
Time Course ◽  
Kinetic Studies ◽  
Discovery Process ◽  
Drug Discovery Process ◽  
Traditional Methods ◽  
Kinetic Relationship

Target engagement by small molecules is necessary for producing a physiological outcome. In the past, a lot of emphasis was placed on understanding the thermodynamics of such interactions to guide structure–activity relationships. It is becoming clearer, however, that understanding the kinetics of the interaction between a small-molecule inhibitor and the biological target [structure–kinetic relationship (SKR)] is critical for selection of the optimum candidate drug molecule for clinical trial. However, the acquisition of kinetic data in a high-throughput manner using traditional methods can be labor intensive, limiting the number of molecules that can be tested. As a result, in-depth kinetic studies are often carried out on only a small number of compounds, and usually at a later stage in the drug discovery process. Fundamentally, kinetic data should be used to drive key decisions much earlier in the drug discovery process, but the throughput limitations of traditional methods preclude this. A major limitation that hampers acquisition of high-throughput kinetic data is the technical challenge in collecting substantially confluent data points for accurate parameter estimation from time course analysis. Here, we describe the use of the fluorescent imaging plate reader (FLIPR), a charge-coupled device (CCD) camera technology, as a potential high-throughput tool for generating biochemical kinetic data with smaller time intervals. Subsequent to the design and optimization of the assay, we demonstrate the collection of highly confluent time-course data for various kinase protein targets with reasonable throughput to enable SKR-guided medicinal chemistry. We select kinase target 1 as a special case study with covalent inhibition, and demonstrate methods for rapid and detailed analysis of the resultant kinetic data for parameter estimation. In conclusion, this approach has the potential to enable rapid kinetic studies to be carried out on hundreds of compounds per week and drive project decisions with kinetic data at an early stage in drug discovery.

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