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Nisha Mulakken

Publications and source records attributed to Nisha Mulakken.

2 recordsLinked to original sources

The urinary metabolite profile of the dietary carcinogen 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine is predictive of colon DNA adducts after a low-dose exposure in humans.

Epidemiologic evidence indicates that exposure to heterocyclic amines in the diet is an important risk factor for the development of colon cancer. Well-done cooked meats contain significant levels of heterocyclic amines, which have been shown to cause cancer in laboratory animals. To better understand the mechanisms of heterocyclic amine bioactivation in humans, the most mass abundant heterocyclic amine, 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP), was used to assess the relationship between PhIP metabolism and DNA adduct formation. Ten human volunteers where administered a dietary relevant dose of [(14)C]PhIP 48 to 72 hours before surgery to remove colon tumors. Urine was collected for 24 hours after dosing for metabolite analysis, and DNA was extracted from colon tissue and analyzed by accelerator mass spectrometry for DNA adducts. All 10 subjects were phenotyped for cytochrome P4501A2 (CYP1A2), N-acetyltransferase 2, and sulfotransferase 1A1 enzyme activity. Twelve PhIP metabolites were detected in the urine samples. The most abundant metabolite in all volunteers was N-hydroxy-PhIP-N(2)-glucuronide. Metabolite levels varied significantly between the volunteers. Interindividual differences in colon DNA adducts levels were observed between each individual. The data showed that individuals with a rapid CYP1A2 phenotype and high levels of urinary N-hydroxy-PhIP-N(2)-glucuronide had the lowest level of colon PhIP-DNA adducts. This suggests that glucuronidation plays a significant role in detoxifying N-hydroxy-PhIP. The levels of urinary N-hydroxy-PhIP-N(2)-glucuronide were negatively correlated to colon DNA adduct levels. Although it is difficult to make definite conclusions from a small data set, the results from this pilot study have encouraged further investigations using a much larger study group.

Arylamine N-Acetyltransferase↗

Comparative genomics tools applied to bioterrorism defence.

Rapid advances in the genomic sequencing of bacteria and viruses over the past few years have made it possible to consider sequencing the genomes of all pathogens that affect humans and the crops and livestock upon which our lives depend. Recent events make it imperative that full genome sequencing be accomplished as soon as possible for pathogens that could be used as weapons of mass destruction or disruption. This sequence information must be exploited to provide rapid and accurate diagnostics to identify pathogens and distinguish them from harmless near-neighbours and hoaxes. The Chem-Bio Non-Proliferation (CBNP) programme of the US Department of Energy (DOE) began a large-scale effort of pathogen detection in early 2000 when it was announced that the DOE would be providing bio-security at the 2002 Winter Olympic Games in Salt Lake City, Utah. Our team at the Lawrence Livermore National Lab (LLNL) was given the task of developing reliable and validated assays for a number of the most likely bioterrorist agents. The short timeline led us to devise a novel system that utilised whole-genome comparison methods to rapidly focus on parts of the pathogen genomes that had a high probability of being unique. Assays developed with this approach have been validated by the Centers for Disease Control (CDC). They were used at the 2002 Winter Olympics, have entered the public health system, and have been in continual use for non-publicised aspects of homeland defence since autumn 2001. Assays have been developed for all major threat list agents for which adequate genomic sequence is available, as well as for other pathogens requested by various government agencies. Collaborations with comparative genomics algorithm developers have enabled our LLNL team to make major advances in pathogen detection, since many of the existing tools simply did not scale well enough to be of practical use for this application. It is hoped that a discussion of a real-life practical application of comparative genomics algorithms may help spur algorithm developers to tackle some of the many remaining problems that need to be addressed. Solutions to these problems will advance a wide range of biological disciplines, only one of which is pathogen detection. For example, exploration in evolution and phylogenetics, annotating gene coding regions, predicting and understanding gene function and regulation, and untangling gene networks all rely on tools for aligning multiple sequences, detecting gene rearrangements and duplications, and visualising genomic data. Two key problems currently needing improved solutions are: (1) aligning incomplete, fragmentary sequence (eg draft genome contigs or arbitrary genome regions) with both complete genomes and other fragmentary sequences; and (2) ordering, aligning and visualising non-colinear gene rearrangements and inversions in addition to the colinear alignments handled by current tools.

Amino Acid Sequence↗