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Biology subjects

Kirsch, B.

Publications and source records attributed to Kirsch, B..

2 recordsLinked to original sources

Barth syndrome cellular models have dysregulated respiratory chain complex I and mitochondrial quality control due to abnormal cardiolipin

Barth syndrome (BTHS) is an X-linked genetic condition caused by defects in TAZ, which encodes a transacylase involved in the remodeling of the inner mitochondrial membrane phospholipid, cardiolipin (CL). As such, CL has been implicated in numerous mitochondrial functions, and the role of defective CL in the clinical pathology of BTHS is under intense investigation. We used untargeted proteomics, shotgun lipidomics, gene expression analysis, and targeted metabolomics to identify novel areas of mitochondrial dysfunction in a new model of TAZ deficiency in HEK293 cells. Functional annotation analysis of proteomics data revealed abnormal regulation of mitochondrial respiratory chain complex I (CI), driven by the reduced abundance of 6 CI associated proteins in TAZ-deficient HEK293 cells: MT-ND3, NDUFA5, NDUFAB1, NDUFB2, NDUFB4, and NDUFAF1. This resulted in reduced assembly and function of CI in TAZ-deficient HEK293 cells as well as BTHS patient derived lymphoblast cells. We also identified increased abundance of PARL, a rhomboid protein involved in the regulation of mitophagy and apoptosis, and abnormal downstream processing of PGAM5, another mediator of mitochondrial quality control, in TAZ-deficient cells. Lastly, we modulated CL via the phospholipase inhibitor bromoenol lactone and the CL targeted SS-peptide, SS-31, and showed that each is able to remediate abnormalities in CI abundance as well as PGAM5 processing. Thus, mitochondrial respiratory chain CI and PARL/PGAM5 regulated mitochondrial quality control, both of whose functions localize to the inner mitochondrial membrane, are dysregulated due to TAZ deficiency and are partially remediated via modulation of CL.

genetics↗

Accuracy of different modalities of reaction time testing: Implications for online cognitive assessment tools.

Reaction time testing is widely used in computerized cognitive assessments, and clinical studies have repeatedly shown it to be a sensitive indicator of cognitive function. Typically, the reaction time test is administered by presenting a subject with a visual stimulus on a computer monitor and prompting the individual to respond (via keypad or computer mouse) as quickly as possible. The individuals reaction time is calculated as the interval between presentation of the stimulus and the time recorded from the mechanical response. However, there are many inherent latencies and variabilities that may be introduced to the measure by both hardware (computer monitor and mouse) and software (operating system). Because of these delays, we hypothesized that a comparison of hardware protocols (excluding human response) would demonstrate significant differences in the resulting reaction time measures. To simulate the delays of various components of the common systems used to obtain reaction time, we conducted a simple experiment in which either a visual or tactile stimulus evoked a movement from a mechanical transducer to respond to a computer peripheral or a dedicated response device. In the first condition, a simulated visual reaction time test was conducted by flashing a visual stimulus on a computer monitor. The stimulus was detected by a dedicated light sensor, and a linear actuator delivered the mechanical response via computer mouse. The second test condition employed a mobile device as the medium for the visual stimulus, and the mechanical response was delivered to the mobile devices touchscreen. The third and fourth test conditions simulated tactile reaction time tests in which the stimulus was generated by a dedicated hardware device. The third condition simulated a tactile stimulus, which was detected by a mechanical switch, and again a hardware device delivered the response via computer mouse. The fourth condition also simulated a tactile stimulus, but the response was delivered by a dedicated hardware device designed to store the interval between stimulus delivery and stimulus response. There were significant differences in the range of responses recorded from the four different conditions with the reaction time collected from a visual stimulus on a mobile device being the worst and the device with dedicated hardware designed for the task being the best. The results suggest that some of the commonly used visual tasks on consumer grade computers could be introducing significant errors for reaction time testing and that dedicated hardware designed for the reaction time task is needed to minimize testing errors.

bioengineering↗