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This chapter discusses fatty acids, the building blocks of lipids, which represent a significant fraction of the total lipid pool in aquatic organisms. It explores how chain length and levels of unsaturation (number of double bonds) have been shown to be correlated to decomposition, indicating a pre- and postdepositional selective loss of short-chain and polyunsaturated fatty acids. In contrast, saturated fatty acids are more stable and typically increase in relative proportion to total fatty acids with increasing sediment depth. Polyunsaturated fatty acids (PUFAs) are predominantly used as proxies for the presence of “fresh” algal sources, although some PUFAs also occur in vascular plants and deep-sea bacteria. Thus, these biomarkers represent a very diverse group of compounds present in aquatic systems. The numerous applications of fatty acid biomarkers to identifying the sources of organic matter in lakes, rivers, estuaries, and marine ecosystems are discussed.

This chapter describes the molecular structures of the three known carbon oxides, the three known sulfur oxides, eight nitrogen oxides, two phosphorus oxides, and three chlorine oxides. Bond energies are presented whenever available. The discussion also includes three sulfur oxofluorides, sulfuric acid, nitric acid, two phosphoryl halides (OPX₃), orthophosphoric acid, and perchlorid acid. Both the bond distances and the bond energies indicate that the terminal oxygen atoms in all the molecules under consideration should be described as doubly bonded (oxo) atoms, the only exception being CO which is best described as triply bonded. The structures are discussed in terms of simple Lewis structures, the VSEPR model, and delocalized π molecular orbitals.

This chapter summarizes the current understanding of how specific carbohydrates are made by glycosyltransferases on glycoproteins in neural cells and the important functions of these carbohydrates in neural development. It also describes recent findings on sulfated carbohydrates and polysialic acid as functional terminal structures in glycoproteins.

Eukaryotic cells are composed of numerous lipids, among which the glycosphingolipids and especially the sialic-acid-containing gangliosides occur ubiquitously in most tissues. They are particularly common in neuroectodermal cells where they comprise up to 6% of the total lipids in central and peripheral nervous tissue membranes. This chapter focuses on the various sialic acid modifications which occur in gangliosides, especially those from neuronal tissues, and which may modulate their biological effect. It describes the structures of the various natural sialic acids and their general metabolic pathway and its subcellular localization. It shows the biosynthesis of the various sialic acids with respect to the modified gangliosides.

Glutamate is an amino acid that your brain uses as a neurotransmitter and it is almost always is excitatory. GABA is also an amino acid that your brain uses as a neurotransmitter and it is almost always inhibitory. These two neurotransmitters are widespread in your brain and tend to compete for turning your neurons on or off. Glutamate makes and breaks connections between neurons; this action allows your brain to learn. For example, if you consume a chemical that blocks the actions of glutamate you become amnestic, unable to remember anything new. The street drugs PCP and ketamine block glutamate receptors and depress the activity of your brain. Your brain makes its own PCP-like neurotransmitter called angeldustin. Chemicals that enhance the action of GABA, such as alcohol, barbiturates, or any of the popular drugs related to Valium and Librium, can make us sleepy, send us into a coma, or kill us by turning off too many neurons in the brain.

Magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) enable the noninvasive regional assessment of major metabolites in the human brain including: N-acetyl aspartate (NAA), glutamate, gamma amino butyric acid (GABA) and phosphocreatine (PCr). In epilepsy, neuronal impairment and bioenergetic alterations result in decreased levels of NAA and PCr in both the primary focus and networks involved in seizure propagation. The alterations in NAA and PCr are not due solely to neuronal loss, but are correlated with functional decline and hiostologic changes at a cellular level, suggesting a significant role for bioenergetic impairment in the pathophysiology of epilepsy. Alterations in brain GABA levels have been used to titrate and evaluate the effectiveness of antiepileptic medications targeting the GABAergic system.

Alpha[¹¹C]Methyl-L-tryptophan (AMT) was developed initially as a tracer for positron emission tomography (PET) in order to measure brain serotonin synthesis, but subsequent studies have shown that it also traces the kynurenine pathway. AMT PET has been applied to the study of several populations of patients being evaluated for epilepsy surgery, including lesional (tuberous sclerosis complex, tumors and malformations of cortical development) and nonlesional cases. It has shown a high specificity, but modest sensitivity, in identifying the epileptic focus in cortical regions. However, AMT PET does not have localizing value in assessment of medial temporal lobe epilepsy. AMT PET has increased our understanding of the kynurenine pathway in epilepsy suggesting new pharmacological approaches.

A probabilistic sequence (PS) is a sequence in which each position instead of having a single character (amino acid, nucleotide, or codon), has a vector describing the probability of each symbol being the character at that position. A probabilistic ancestral sequence (PAS) is a reconstructed PS for the common ancestor of several sequences. This chapter presents a formalism to compute the probabilities of each character at each position of the biological sequence for the internal nodes in a given phylogenetic tree using a Markov model of evolution. From this model, the probability of an evolutionary configuration can be computed. In addition, efficient algorithms for computing the likelihood score of aligning a character with a character, a character with a probabilistic character, or two probabilistic characters are derived. These scores can then be used in direct string matching or dynamic programming alignments of probabilistic sequences with insertions and deletions. Applications for these alignments, including long-distance homology searching and multiple sequence alignment construction, are shown.

The goal of ancestral inference is to have as accurate a picture of ancestral function as possible. Thus, it is worthwhile to try to understand the nature and cause of the sequence and functional bias, and how to overcome this bias. This chapter argues that the bias inherent in in the choice to reconstruct the ancestral sequence with the highest posterior probability, along with the optimization bias due to site-specific model inaccuracy, may have biased the frequencies with which certain amino acids are inferred. Amino acids that tend to have consistently low posterior probabilities are most probably undersampled. A simple strategy to address amino acid sampling bias when reconstructing ancestral proteins in the laboratory is discussed.

The paucity of cultural finds at this key stage in human prehistory increases the need to fully and effectively exploit all the sources of evidence that exist. Organic residues, preserved in association with skeletal remains and pottery, have the potential to provide various levels of information relating to diet and subsistence, and thus the wider interactions of ancient humans with their environment. This chapter explores the potential to enhance the rigour and level of information retrievable from the biochemical constituents of skeletal remains and pottery by exploiting new sources of molecular and isotopic information. It addresses the following possibilities: (i) deriving palaeodietary information from human remains via the complementary use of amino acid and lipid components; and (ii) assessing terrestrial and marine contributions to organic residues preserved in skeletal remains and pottery.

This chapter presents a new approach to functional divergence analysis with the combination of ancestral sequence inference, using the family of animal G-protein subunits as an example. Using the method, the evolutionary trends of two types of functional divergence of amino acid residues after gene duplication are traced. These pieces of evolutionary information are useful for making testable hypotheses about functional divergence between protein subfamilies, such as subtypes of G-protein subunits, which can be verified by further experimentation.

The last universal ancestor (LUA) represents a relatively accessible theoretical intermediary between extant cellular organisms and early, precellular ‘life’. In a previous study, the expectation-maximization (EM) approach was used to infer ancestral amino acid frequencies, where in each iteration expected counts were derived from posterior distributions at each site. Applying this approach to estimate the amino acid composition of 65 proteins in the LUA showed that composition was more similar to that of extant thermophiles than mesophiles. This chapter examines whether the previous result is robust with respect to the OGT of the taxa used to infer the amino acid composition of proteins in the LUA. It is shown that even if only mesophilic species are used to derive the estimated ancestral amino acid composition, that composition is most similar to that of thermophiles, as measured by Euclidean distance. The relative mean Euclidean distance between the amino acid composition in any one species and that of a set of mesophiles or thermophiles can be used unequivocally to classify it. Thus, the inferred amino acid composition in the LUA allows its classification as a thermophile.

This concluding chapter discusses the various issues raised in the course of the book and suggests a way forward for readers attempting ancestral sequence reconstruction. Ancestral sequence reconstruction can be used for testing general hypotheses about the environment and lifestyles of extinct species, general hypotheses about the processes driving gene and genome evolution, specific hypotheses about the evolution of gene function in individual gene families, and ultimately the it can be used for the generation of an understanding of the mapping between sequence (and substitution) to molecular function. A consideration of alternative phylogenetic tree topologies and their effects on ancestral sequence reconstruction is recommended. For smaller data-sets, integrated methods that combine multiple sequence alignment and phylogenetic tree construction in one step are slow, but may provide a better assessment of homology and the evolutionary history of any given amino acid position. Readers may also consider starting with precalculated gene families that already contain multiple sequence alignments and phylogenetic trees for families of interest. Such families can be modified with detailed knowledge and expanded to include new sequences, as available and desired.

This chapter discusses proteins, which make up approximately 50% of organic matter and contain about 85% of the organic nitrogen in marine organisms. Peptides and proteins comprise an important fraction of the particulate organic carbon (13–37%) and particulate organic nitrogen (30–81%), as well as dissolved organic nitrogen (5–20%) and dissolved organic carbon (3–4%) in oceanic and coastal waters. In sediments, proteins account for approximately 7 to 25% of organic carbon and an estimated 30 to 90% of total nitrogen. Amino acids are the basic building blocks of proteins. This class of compounds is essential to all organisms and represents one of the most important components in the organic nitrogen cycle. Amino acids represent one of the most labile pools of organic carbon and nitrogen.