A Comparative Study on Three Analytical Methods for the Determination of the Neurotoxin BMAA in Cyanobacteria

The cyanobacterial neurotoxin β-N-methylamino-L-alanine (BMAA) has been considered a serious health threat because of its putative role in multiple neurodegenerative diseases. First reports on BMAA concentrations in cyanobacteria were alarming: nearly all cyanobacteria were assumed to contain high BMAA concentrations, implying ubiquitous exposure. Recent studies however question this presence of high BMAA concentrations in cyanobacteria. To assess the real risk of BMAA to human health, this discrepancy must be resolved. We therefore tested whether the differences found could be caused by the analytical methods used in different studies. Eight cyanobacterial samples and two control samples were analyzed by three commonly used methods: HPLC-FLD analysis and LC-MS/MS analysis of both derivatized and underivatized samples. In line with published results, HPLC-FLD detected relatively high BMAA concentrations in some cyanobacterial samples, while both LC-MS/MS methods only detected BMAA in the positive control (cycad seed sarcotesta). Because we could eliminate the use of different samples and treatments as causal factors, we demonstrate that the observed differences were caused by the analytical methods. We conclude that HPLC-FLD overestimated BMAA concentrations in some cyanobacterial samples due to its low selectivity and propose that BMAA might be present in (some) cyanobacteria, but in the low µg/g or ng/g range instead of the high µg/g range as sometimes reported before. We therefore recommend to use only selective and sensitive analytical methods like LC-MS/MS for BMAA analysis. Although possibly present in low concentrations in cyanobacteria, BMAA can still form a health risk. Recent evidence on BMAA accumulation in aquatic food chains suggests human exposure through consumption of fish and shellfish which expectedly exceeds exposure through cyanobacteria

Does α-Amino-β-methylaminopropionic Acid (BMAA) Play a Role in Neurodegeneration?

The association of α-amino-β-methylaminopropionic acid (BMAA) with elevated incidence of amyotrophic lateral sclerosis/Parkinson’s disease complex (ALS/PDC) was first identified on the island of Guam. BMAA has been shown to be produced across the cyanobacterial order and its detection has been reported in a variety of aquatic and terrestrial environments worldwide, suggesting that it is ubiquitous. Various in vivo studies on rats, mice, chicks and monkeys have shown that it can cause neurodegenerative symptoms such as ataxia and convulsions. Zebrafish research has also shown disruption to neural development after BMAA exposure. In vitro studies on mice, rats and leeches have shown that BMAA acts predominantly on motor neurons. Observed increases in the generation of reactive oxygen species (ROS) and Ca2+ influx, coupled with disruption to mitochondrial activity and general neuronal death, indicate that the main mode of activity is via excitotoxic mechanisms. The current review pertaining to the neurotoxicity of BMAA clearly demonstrates its ability to adversely affect neural tissues, and implicates it as a potentially significant compound in the aetiology of neurodegenerative disease. When considering the potential adverse health effects upon exposure to this compound, further research to better understand the modes of toxicity of BMAA and the environmental exposure limits is essential

Grazing livestock are exposed to terrestrial cyanobacteria

While toxins from aquatic cyanobacteria are a well-recognised cause of disease in birds and animals, exposure of grazing livestock to terrestrial cyanobacteria has not been described. This study identified terrestrial cyanobacteria, predominantlyPhormidiumspp., in the biofilm of plants from most livestock fields investigated. Lower numbers of other cyanobacteria, microalgae and fungi were present on many plants. Cyanobacterial 16S rDNA, predominantly fromPhormidiumspp., was detected in all samples tested, including 6 plant washings, 1 soil sample and ileal contents from 2 grazing horses. Further work was performed to test the hypothesis that ingestion of cyanotoxins contributes to the pathogenesis of some currently unexplained diseases of grazing horses, including equine grass sickness (EGS), equine motor neuron disease (EMND) and hepatopathy.Phormidiumpopulation density was significantly higher on EGS fields than on control fields. The cyanobacterial neurotoxic amino acid 2,4-diaminobutyric acid (DAB) was detected in plant washings from EGS fields, but worst case scenario estimations suggested the dose would be insufficient to cause disease. Neither DAB nor the cyanobacterial neurotoxins β-N-methylamino-L-alanine and N-(2-aminoethyl) glycine were detected in neural tissue from 6 EGS horses, 2 EMND horses and 7 control horses.Phormidiumwas present in low numbers on plants where horses had unexplained hepatopathy. This study did not yield evidence linking known cyanotoxins with disease in grazing horses. However, further study is warranted to identify and quantify toxins produced by cyanobacteria on livestock fields, and determine whether, under appropriate conditions, known or unknown cyanotoxins contribute to currently unexplained diseases in grazing livestock

Dynamic Changes in Protein Functional Linkage Networks Revealed by Integration with Gene Expression Data

Response of cells to changing environmental conditions is governed by the dynamics of intricate biomolecular interactions. It may be reasonable to assume, proteins being the dominant macromolecules that carry out routine cellular functions, that understanding the dynamics of protein∶protein interactions might yield useful insights into the cellular responses. The large-scale protein interaction data sets are, however, unable to capture the changes in the profile of protein∶protein interactions. In order to understand how these interactions change dynamically, we have constructed conditional protein linkages for Escherichia coli by integrating functional linkages and gene expression information. As a case study, we have chosen to analyze UV exposure in wild-type and SOS deficient E. coli at 20 minutes post irradiation. The conditional networks exhibit similar topological properties. Although the global topological properties of the networks are similar, many subtle local changes are observed, which are suggestive of the cellular response to the perturbations. Some such changes correspond to differences in the path lengths among the nodes of carbohydrate metabolism correlating with its loss in efficiency in the UV treated cells. Similarly, expression of hubs under unique conditions reflects the importance of these genes. Various centrality measures applied to the networks indicate increased importance for replication, repair, and other stress proteins for the cells under UV treatment, as anticipated. We thus propose a novel approach for studying an organism at the systems level by integrating genome-wide functional linkages and the gene expression data

Is Neurodegenerative Disease a Long-Latency Response to Early-Life Genotoxin Exposure?

Western Pacific amyotrophic lateral sclerosis and parkinsonism-dementia complex, a disappearing neurodegenerative disease linked to use of the neurotoxic cycad plant for food and/or medicine, is intensively studied because the neuropathology (tauopathy) is similar to that of Alzheimer’s disease. Cycads contain neurotoxic and genotoxic principles, notably cycasin and methylazoxymethanol, the latter sharing chemical relations with nitrosamines, which are derived from nitrates and nitrites in preserved meats and fertilizers, and also used in the rubber and leather industries. This review includes new data that influence understanding of the neurobiological actions of cycad and related genotoxins and the putative mechanisms by which they might trigger neurodegenerative disease

DAG-informed regression modelling, agent-based modelling, and microsimulation modelling: A critical comparison of methods for causal inference

The current paradigm for causal inference in epidemiology relies primarily on the evaluation of counterfactual contrasts via statistical regression models informed by graphical causal models (often in the form of directed acyclic graphs, or DAGs) and their underlying mathematical theory. However, there have been growing calls for supplementary methods, and one such method that has been proposed is agent-based modelling due to its potential for simulating counterfactuals. However, within the epidemiological literature there currently exists a general lack of clarity regarding what exactly agent-based modelling is (and is not) and, importantly, how it differs from microsimulation modelling – perhaps its closest methodological comparator. We clarify this distinction by briefly reviewing the history of each method, which provides context for their similarities and differences, and casts light on the types of research questions that they have evolved (and thus are well-suited) to answering; we do the same for DAG-informed regression methods. The distinct historical evolutions of DAG-informed regression modelling, microsimulation modelling, and agent-based modelling have given rise to distinct features of the methods themselves, and provide a foundation for critical comparison. Not only are the three methods well-suited to addressing different types of causal questions, but in doing so they place differing levels of emphasis on fixed and random effects, and also tend to operate on different timescales and in different timeframes