Transmission Of Intra-cellular Genetic Information: A System Proposal.

One of the great challenges of the scientific community on theories of genetic information, genetic communication and genetic coding is to determine a mathematical structure related to DNA sequences. In this paper we propose a model of an intra-cellular transmission system of genetic information similar to a model of a power and bandwidth efficient digital communication system in order to identify a mathematical structure in DNA sequences where such sequences are biologically relevant. The model of a transmission system of genetic information is concerned with the identification, reproduction and mathematical classification of the nucleotide sequence of single stranded DNA by the genetic encoder. Hence, a genetic encoder is devised where labelings and cyclic codes are established. The establishment of the algebraic structure of the corresponding codes alphabets, mappings, labelings, primitive polynomials (p(x)) and code generator polynomials (g(x)) are quite important in characterizing error-correcting codes subclasses of G-linear codes. These latter codes are useful for the identification, reproduction and mathematical classification of DNA sequences. The characterization of this model may contribute to the development of a methodology that can be applied in mutational analysis and polymorphisms, production of new drugs and genetic improvement, among other things, resulting in the reduction of time and laboratory costs.

Bioremediation Potential Of Microorganisms Derived From Petroleum Reservoirs.

Bacterial strains and metagenomic clones, both obtained from petroleum reservoirs, were evaluated for petroleum degradation abilities either individually or in pools using seawater microcosms for 21 days. Gas Chromatography-Flame Ionization Detector (GC-FID) and Gas Chromatography-Mass Spectrometry (GC-MS) analyses were carried out to evaluate crude oil degradation. The results showed that metagenomic clones 1A and 2B were able to biodegrade n-alkanes (C14 to C33) and isoprenoids (phytane and pristane), with rates ranging from 31% to 47%, respectively. The bacteria Dietzia maris CBMAI 705 and Micrococcus sp. CBMAI 636 showed higher rates reaching 99% after 21 days. The metagenomic clone pool biodegraded these compounds at rates ranging from 11% to 45%. Regarding aromatic compound biodegradation, metagenomic clones 2B and 10A were able to biodegrade up to 94% of phenanthrene and methylphenanthrenes (3-MP, 2-MP, 9-MP and 1-MP) with rates ranging from 55% to 70% after 21 days, while the bacteria Dietzia maris CBMAI 705 and Micrococcus sp. CBMAI 636 were able to biodegrade 63% and up to 99% of phenanthrene, respectively, and methylphenanthrenes (3-MP, 2-MP, 9-MP and 1-MP) with rates ranging from 23% to 99% after 21 days. In this work, isolated strains as well as metagenomic clones were capable of degrading several petroleum compounds, revealing an innovative strategy and a great potential for further biotechnological and bioremediation applications.

A Metabolomic Protocol For Plant Systematics By Matrix-assisted Laser-desorption/ionization Time-of Flight Mass Spectrometry.

Matrix-assisted laser desorption/ionization time-of flight mass spectrometry (MALDI-TOF MS) has been widely used for the identification and classification of microorganisms based on their proteomic fingerprints. However, the use of MALDI-TOF MS in plant research has been very limited. In the present study, a first protocol is proposed for metabolic fingerprinting by MALDI-TOF MS using three different MALDI matrices with subsequent multivariate data analysis by in-house algorithms implemented in the R environment for the taxonomic classification of plants from different genera, families and orders. By merging the data acquired with different matrices, different ionization modes and using careful algorithms and parameter selection, we demonstrate that a close taxonomic classification can be achieved based on plant metabolic fingerprints, with 92% similarity to the taxonomic classifications found in literature. The present work therefore highlights the great potential of applying MALDI-TOF MS for the taxonomic classification of plants and, furthermore, provides a preliminary foundation for future research.