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2.8: Dictionaries - Biology

2.8: Dictionaries - Biology


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Dictionaries (often called “hash tables” in other languages) are an efficient and incredibly useful way to associate data with other data. Consider a list, which associates each data element in the list with an integer starting at zero:

A dictionary works in much the same way, except instead of indices, dictionaries use “keys,” which may be integers or strings.[1] We’ll usually draw dictionaries longwise, and include the keys within the illustrating brackets, because they are as much a part of the dictionary structure as the values:

Let’s create a dictionary holding these keys and values with some code, calling itids_to_gcs. Note that this name encodes both what the keys and values represent, which can be handy when keeping track of the contents of these structures. To create an empty dictionary, we call thedict()function with no parameters, which returns the empty dictionary. Then, we can assign and retrieve values much like we do with lists, except (1) we’ll be using strings as keys instead of integer indices, and (2) we can assign values to keys even if the key is not already present.

We can then access individual values just like with a list:

However, we cannot access a value for a key that doesn’t exist. This will result in aKeyError, and the program will halt.

Dictionaries go one way only: given the key, we can look up the value, but given a value, we can’t easily find the corresponding key. Also, the name “dictionary” is a bit misleading, because although real dictionaries are sorted in alphabetical order, Python dictionaries have no intrinsic order. Unlike lists, which are ordered and have a first and last element, Python makes no guarantees about how the key/value pairs are stored internally. Also, each unique key can only be present once in the dictionary and associated with one value, though that value might be something complex like a list, or even another dictionary. Perhaps a better analogy would be a set of labeled shelves, where each label can only be used once.

There are a variety of functions and methods that we can use to operate on dictionaries in Python. For example, thelen()function will return the number of key/value pairs in a dictionary. For the dictionary above,len(ids_to_gcs)will return3. If we want, we can get a list of all the keys in a dictionary using its.keys()method, though this list may be in a random order because dictionaries are unordered. We could always sort the list, and loop over that:

Similarly, we can get a list of all the values using.values(), again in no particular order. So,ids_to_gcs.values()will return a list of three floats.[2]

If we try to get a value for a key that isn’t present in the dictionary, we’ll get aKeyError. So, we will usually want to test whether a key is present before attempting to read its value. We can do this with the dictionary’s.has_key()method, which returnsTrueif the key is present in the dictionary.[3]

Counting Gene Ontology Terms

To illustrate the usage of a dictionary in practice, consider the file PZ.annot.txt, the result of annotating a set of assembled transcripts with gene ontology (GO) terms and numbers. Each tab-separated line gives a gene ID, an annotation with a GO number, and a corresponding human-readable term associated with that number.

In this file, each gene may be associated with multiple GO numbers, and each GO number may be associated with multiple genes. Further, each GO term may be associated with multiple different GO numbers. How many times is each ID found in this file? Ideally, we’d like to produce tab-separated output that looks like so:

Our strategy: To practice some of the command line interaction concepts, we’ll have this program read the file on standard input and write its output to standard output (as discussed in chapter 19, “Command Line Interfacing”). We’ll need to keep a dictionary, where the keys are the gene IDs and the values are the counts. A for-loop will do to read in each line, stripping off the ending newline and splitting the result into a list on the tab character, . If the ID is in the dictionary, we’ll add one to the value. Because the dictionary will start empty, we will frequently run into IDs that aren’t already present in the dictionary; in these cases we can set the value to1. Once we have processed the entire input, we can loop over the dictionary printing each count and ID.

In the code below (go_id_count.py), when the dictionary has theseqidkey, we’re both reading from the dictionary (on the right-hand side) and writing to the value (on the left-hand side).

But when the key is not present, we’re simply writing to the value. In the loop that prints the dictionary contents, we are not checking for the presence of eachidbefore reading it to print, because the list ofids_listis guaranteed to contain exactly those keys that are in the dictionary, as it is the result ofids_to_counts.keys().

What’s the advantage of organizing our Python program to read rows and columns on standard input and write rows and columns to standard output? Well, if we know the built-in command line tools well enough, we can utilize them along with our program for other analyses. For example, we can first filter the data withgrepto select those lines that match the termtranscriptase:

The result is only lines containing the word “transcriptase”:

If we then feed those results through our program (cat PZ.annot.txt | grep 'transcriptase' | ./go_id_count.py), we see only counts for IDs among those lines.

Finally, we could pipe the results throughwcto count these lines and determine how many IDs were annotated at least once with that term (21). If we wanted to instead see which eight genes had the most annotations matching “transcriptase,” we could do that, too, by sorting on the counts and usingheadto print the top eight lines (here we’re breaking up the long command with backslashes, which allow us to continue typing on the next line in the terminal).[4]

It appears genePZ32722_Bhas been annotated as a transcriptase seven times. This example illustrates that, as we work and build tools, if we consider how they might interact with other tools (even other pieces of code, like functions), we can increase our efficiency remarkably.

Extracting All Lines Matching a Set of IDs

Another useful property of dictionaries is that the.has_key()method is very efficient. Suppose we had an unordered list of strings, and we wanted to determine whether a particular string occurred in the list. This can be done, but it would require looking at each element (in a for-loop, perhaps) to see if it equaled the one we are searching for. If we instead stored the strings as keys in a dictionary (storing"present", or the number1, or anything else in the value), we could use the.has_key()method, which takes a single time step (effectively, on average) no matter how many keys are in the dictionary.[5]

Returning to the GO/ID list from the last example, suppose that we had the following problem: we wish to first identify all those genes (rows in the table) that were labeled withGO:0001539(which we can do easily withgrepon the command line), and then we wish to extract all rows from the table matching those IDs to get an idea of what other annotations those genes might have.

In essence, we want to print all entries of a file:

Where the first column matches any ID in the first column of another input:

As it turns out, the above problem is common in data analysis (subsetting lines on the basis of an input “query” set), so we’ll be careful to design a program that is not specific to this data set, except that the IDs in question are found in the first column.[6]

We’ll write a program calledmatch_1st_cols.pythat takes two inputs: on standard input, it will read a number of lines that have the query IDs we wish to extract, and it will also take a parameter that specifies the file from which matching lines should be printed. For this instance, we would like to be able to execute our program as follows:

In terms of code, the program can first read the input from standard input and create a dictionary that has keys corresponding to each ID that we wish to extract (the values can be anything). Next, the program will loop over the lines of the input file (specified insys.argv[1]), and for each ID check it with.has_key()against the dictionary created previously; if it’s found, the line is printed.

Making the program (match_1st_cols.py) executable and running it reveals all annotations for those IDs that are annotated withGO:0001539.

As before, we can use this strategy to easily extract all the lines matching a variety of criteria, just by modifying one or both inputs. Given any list of gene IDs of interest from a collaborator, for example, we could use that on the standard input and extract the corresponding lines from the GO file.

Exercises

  1. Dictionaries are often used for simple lookups. For example, a dictionary might have keys for all three base-pair DNA sequences ("TGG","GCC","TAG", and so on) whose values correspond to amino acid codes (correspondingly,"W","A","*"for “stop,” and so on). The full table can be found on the web by searching for “amino acid codon table.”

    Write a function calledcodon_to_aa()that takes in a single three-base-pair string and returns a one-character string with the corresponding amino acid code. You may need to define all 64 possibilities, so be careful not to make any typos! If the input is not a valid three-base-pair DNA string, the function should return"X"to signify “unknown.” Test your function with a few calls likeprint(codon_to_aa("TGG")),print(codon_to_aa("TAA")), andprint(codon_to_aa("BOB")).

  2. Combine the result of thecodon_to_aa()function above with theget_windows()function from the exercises in chapter 18, “Python Functions,” to produce adna_to_aa()function. Given a string like"AAACTGTCTCTA", the function should return its translation as"KLSL".
  3. Use theget_windows()function to write acount_kmers()function; it should take two parameters (a DNA sequence and an integer) and return a dictionary of k-mers to count for those k-mers. For example,count_kmers("AAACTGTCTCTA", 3)should return a dictionary with keys"AAA","AAC","ACT","CTG","TGT","GTC","TCT","CTC","CTA"and corresponding values1,1,1,1,1,1,2,1,1. (K-mer counting is an important step in many bioinformatics algorithms, including genome assembly.)
  4. Create a functionunion_dictionaries()that takes two dictionaries as parameters returns their “union” as a dictionary—when a key is found in both, the larger value should be used in the output. If dictionarydict_amaps"A","B","C"to3,2,6, anddict_bmaps"B","C","D"to7,4,1, for example, the output should map"A","B","C","D"to3,7,6,1.


2.8: Dictionaries - Biology

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Background

Biology is undergoing a paradigm shift due to the introduction of single-cell sequencing methods [1,2,3,4,5]. The cell is the fundamental unit of biological systems, and studying thousands of them individually allows reconstruction of the cellular diversity and dynamics formerly blended into bulk tissue samples. For instance, single-cell transcriptomics (or scRNA-seq) allows the measurement of the expression of thousands of mRNAs from potentially hundreds of thousands of individual cells. The mRNAs of each cell are indicative of the cell type or state and allow biological questions to be addressed at a new level of integration and detail. From the sequencing of a single cell in 2009 [6], we have seen year-on-year exponential increases in the number of cells that can be sampled by scRNA-seq [7]. Using these methods, scientists have already profiled a broad taxonomic range of different animals, classified their cell types, profiled their gene expression patterns, and begun to reconstruct their cell differentiation lineages. Single-cell transcriptomics has been already used in very diverse animal groups, including sponges [8, 9], cnidarians [10, 11], placozoans [9], ctenophores [9], planarians [12,13,14,15,16], nematodes [17, 18], arthropods [19,20,21,22], ascidians [23], and extensively in vertebrates [24,25,26,27,28,29,30,31].

Currently, the most popular methods are based on droplet-based barcoding: encapsulating single cells with oligonucleotide barcodes in nanolitre droplets [32, 33]. One of the most promising recent developments involves employing combinatorial barcoding techniques [17, 34], which use the cells themselves as reaction chambers. These approaches label cellular mRNAs through successive rounds of mixing and pooling the cell population such that the probability of two cells receiving the same barcode combination is minimized. The implementation of combinatorial barcoding methods allows the generation of datasets containing millions of cells from different samples [25, 35].

One major technical hurdle of single-cell transcriptomic approaches is the lack of a cell dissociation method that simultaneously fixes the cells and preserves mRNAs. Typically, dissociation is done in live cells and relies on enzymatic (e.g., trypsin, papain, or similar) or mechanical (e.g., dounce homogenization) approaches [36], which introduce dissociation artifacts and cellular stress on the samples [37,38,39]. Dissociated cells are stripped from their extracellular context and washed, incubated, centrifuged, stained, and often sorted by FACS while still alive, which changes their gene expression patterns. Preservation can only take place hours after the beginning of the experiment, but this time suffices for the activation of stress responses [38]. The use of cold-active proteases obtained from psychrophilic organisms has been proposed as an alternative approach [40]. Another alternative is obtaining single-cell transcriptomic data from the nuclei [41, 42], as these can be extracted from frozen tissue [25]. However, this approach eliminates the majority of mature mRNAs, as these concentrate outside the nucleus. The introduction of a method that simultaneously fixes and dissociates cells, preserving their RNA, is a critical need of the single-cell transcriptomic field.

To overcome the limitations of live cell dissociations, we have developed ACME dissociation. Our protocol is based on a nineteenth-century dissociation protocol—often called “maceration”—with modifications to make it compatible with modern single-cell transcriptomics. The maceration procedure was first used by Schneider in 1890 [43]. It was then used throughout the twentieth century to dissociate cells of animals such as cnidarians [44] and planarians [45] and observe them under the microscope but is now rarely used [46, 47]. In its original form, the maceration solution simply consisted of acetic acid and glycerol dissolved in water. Baguñà and Romero added methanol as it preserved better morphology [45]. Our protocol uses acetic acid and methanol, together with glycerol, dissolved in water. This solution produces fixed single cells in suspension with high-integrity RNAs. Conveniently, we show that ACME-dissociated cells can be cryopreserved using DMSO [48] at different points throughout the process, with little detriment to their recovery and RNA integrity. We also show that ACME can be used as a fixative, rendering RNA with an integrity superior to that obtained by formaldehyde. As a proof of principle, we have obtained single-cell transcriptomic data from different species and with different single-cell transcriptomic platforms using ACME-dissociated cells. First, we obtained 3899 cells from the cnidarian Nematostella vectensis, using a droplet-based method. With this, we recover all major cell types described in a previous study [10]. Second, we combined ACME with a modified version of split pool ligation-based transcriptome sequencing (SPLiT-seq) [34], a combinatorial indexing method, and were able to profile 33,827 cells from two different planarian species, Schmidtea mediterranea and Dugesia japonica, in a single run. We recover all S. mediterranea cell types from a previous study [13], at comparable proportions, showing that ACME dissociation does not introduce biases in cell type composition. Furthermore, we describe for the first time the single-cell transcriptome of D. japonica, opening the study of cell type evolution in this clade. We integrate our analysis with previous S. mediterranea data obtained by trypsin dissociation, showing that the datasets are broadly compatible and can be integrated in a straightforward manner. Altogether, in combination with droplet-based or combinatorial barcoding platforms such as SPLiT-seq, ACME dissociation is a robust method to obtain high-quality single-cell transcriptomic data from fixed cells.


What Is the Bottleneck Effect in Biology?

A bottleneck effect is an ecological phenomenon in which the population of a species is drastically reduced to the point where the species is still able to carry on, but the genetic diversity of the species is severely limited. This type of event only occurs when members of the population are killed at random, and their death has nothing to do with genetic flaws or inability to adapt.

There are a very specific set of events that can cause a bottleneck effect, because bottlenecks can only be caused by factors that kill members of the population indiscriminately. If a plague sweeps through a population and kills individuals who have a certain genetic makeup more than others, it cannot be considered a bottleneck situation because it is simply natural selection. Bottlenecks usually occur after earthquakes, tsunamis or overhunting, because these events kill indifferently.

Bottlenecks are harmful to populations because they leave only a few members of the species left to reproduce. This means much of the gene pool is lost and the species must be rebuilt from the genetic makeup of only a few individuals. This lack of genetic diversity occasionally makes populations more susceptible to genetic conditions or diseases.

A classic example of a bottleneck is the elephant seal population, which was hunted almost to extinction, explains a University of California website. The species managed to rebuild its population from only 20 members, but scientists have compared the hunted population to another population which was not hunted to the same extent, and found the hunted population had less genetic diversity.


Contents

Some of the most important discoveries relating to transferases occurred as early as the 1930s. Earliest discoveries of transferase activity occurred in other classifications of enzymes, including beta-galactosidase, protease, and acid/base phosphatase. Prior to the realization that individual enzymes were capable of such a task, it was believed that two or more enzymes enacted functional group transfers. [8]

Transamination, or the transfer of an amine (or NH2) group from an amino acid to a keto acid by an aminotransferase (also known as a "transaminase"), was first noted in 1930 by Dorothy M. Needham, after observing the disappearance of glutamic acid added to pigeon breast muscle. [9] This observance was later verified by the discovery of its reaction mechanism by Braunstein and Kritzmann in 1937. [10] Their analysis showed that this reversible reaction could be applied to other tissues. [11] This assertion was validated by Rudolf Schoenheimer's work with radioisotopes as tracers in 1937. [12] [13] This in turn would pave the way for the possibility that similar transfers were a primary means of producing most amino acids via amino transfer. [14]

Another such example of early transferase research and later reclassification involved the discovery of uridyl transferase. In 1953, the enzyme UDP-glucose pyrophosphorylase was shown to be a transferase, when it was found that it could reversibly produce UTP and G1P from UDP-glucose and an organic pyrophosphate. [15]

Another example of historical significance relating to transferase is the discovery of the mechanism of catecholamine breakdown by catechol-O-methyltransferase. This discovery was a large part of the reason for Julius Axelrod’s 1970 Nobel Prize in Physiology or Medicine (shared with Sir Bernard Katz and Ulf von Euler). [16]

Classification of transferases continues to this day, with new ones being discovered frequently. [17] [18] An example of this is Pipe, a sulfotransferase involved in the dorsal-ventral patterning of Drosophilia. [19] Initially, the exact mechanism of Pipe was unknown, due to a lack of information on its substrate. [20] Research into Pipe's catalytic activity eliminated the likelihood of it being a heparan sulfate glycosaminoglycan. [21] Further research has shown that Pipe targets the ovarian structures for sulfation. [22] Pipe is currently classified as a Drosophilia heparan sulfate 2-O-sulfotransferase. [23]

Systematic names of transferases are constructed in the form of "donor:acceptor grouptransferase." [24] For example, methylamine:L-glutamate N-methyltransferase would be the standard naming convention for the transferase methylamine-glutamate N-methyltransferase, where methylamine is the donor, L-glutamate is the acceptor, and methyltransferase is the EC category grouping. This same action by the transferase can be illustrated as follows:

However, other accepted names are more frequently used for transferases, and are often formed as "acceptor grouptransferase" or "donor grouptransferase." For example, a DNA methyltransferase is a transferase that catalyzes the transfer of a methyl group to a DNA acceptor. In practice, many molecules are not referred to using this terminology due to more prevalent common names. [26] For example, RNA polymerase is the modern common name for what was formerly known as RNA nucleotidyltransferase, a kind of nucleotidyl transferase that transfers nucleotides to the 3’ end of a growing RNA strand. [27] In the EC system of classification, the accepted name for RNA polymerase is DNA-directed RNA polymerase. [28]

Described primarily based on the type of biochemical group transferred, transferases can be divided into ten categories (based on the EC Number classification). [29] These categories comprise over 450 different unique enzymes. [30] In the EC numbering system, transferases have been given a classification of EC2. Hydrogen is not considered a functional group when it comes to transferase targets instead, hydrogen transfer is included under oxidoreductases, [30] due to electron transfer considerations.

Classification of transferases into subclasses
EC number Examples Group(s) transferred
EC 2.1 methyltransferase and formyltransferase single-carbon groups
EC 2.2 transketolase and transaldolase aldehyde or ketone groups
EC 2.3 acyltransferase acyl groups or groups that become alkyl groups during transfer
EC 2.4 glycosyltransferase, hexosyltransferase, and pentosyltransferase glycosyl groups, as well as hexoses and pentoses
EC 2.5 riboflavin synthase and chlorophyll synthase alkyl or aryl groups, other than methyl groups
EC 2.6 transaminase, and oximinotransferase nitrogenous groups
EC 2.7 phosphotransferase, polymerase, and kinase phosphorus-containing groups subclasses are based on the acceptor (e.g. alcohol, carboxyl, etc.)
EC 2.8 sulfurtransferase and sulfotransferase sulfur-containing groups
EC 2.9 selenotransferase selenium-containing groups
EC 2.10 molybdenumtransferase and tungstentransferase molybdenum or tungsten

EC 2.1: single carbon transferases Edit

EC 2.1 includes enzymes that transfer single-carbon groups. This category consists of transfers of methyl, hydroxymethyl, formyl, carboxy, carbamoyl, and amido groups. [31] Carbamoyltransferases, as an example, transfer a carbamoyl group from one molecule to another. [32] Carbamoyl groups follow the formula NH2CO. [33] In ATCase such a transfer is written as carbamoyl phosphate + L-aspartate → L-carbamoyl aspartate + phosphate. [34]

EC 2.2: aldehyde and ketone transferases Edit

Enzymes that transfer aldehyde or ketone groups and included in EC 2.2. This category consists of various transketolases and transaldolases. [35] Transaldolase, the namesake of aldehyde transferases, is an important part of the pentose phosphate pathway. [36] The reaction it catalyzes consists of a transfer of a dihydroxyacetone functional group to glyceraldehyde 3-phosphate (also known as G3P). The reaction is as follows: sedoheptulose 7-phosphate + glyceraldehyde 3-phosphate ⇌ erythrose 4-phosphate + fructose 6-phosphate. [37]

EC 2.3: acyl transferases Edit

Transfer of acyl groups or acyl groups that become alkyl groups during the process of being transferred are key aspects of EC 2.3. Further, this category also differentiates between amino-acyl and non-amino-acyl groups. Peptidyl transferase is a ribozyme that facilitates formation of peptide bonds during translation. [38] As an aminoacyltransferase, it catalyzes the transfer of a peptide to an aminoacyl-tRNA, following this reaction: peptidyl-tRNAA + aminoacyl-tRNABtRNAA + peptidyl aminoacyl-tRNAB. [39]

EC 2.4: glycosyl, hexosyl, and pentosyl transferases Edit

EC 2.4 includes enzymes that transfer glycosyl groups, as well as those that transfer hexose and pentose. Glycosyltransferase is a subcategory of EC 2.4 transferases that is involved in biosynthesis of disaccharides and polysaccharides through transfer of monosaccharides to other molecules. [40] An example of a prominent glycosyltransferase is lactose synthase which is a dimer possessing two protein subunits. Its primary action is to produce lactose from glucose and UDP-galactose. [41] This occurs via the following pathway: UDP-β-D-galactose + D-glucose ⇌ UDP + lactose. [42]

EC 2.5: alkyl and aryl transferases Edit

EC 2.5 relates to enzymes that transfer alkyl or aryl groups, but does not include methyl groups. This is in contrast to functional groups that become alkyl groups when transferred, as those are included in EC 2.3. EC 2.5 currently only possesses one sub-class: Alkyl and aryl transferases. [43] Cysteine synthase, for example, catalyzes the formation of acetic acids and cysteine from O3-acetyl-L-serine and hydrogen sulfide: O3-acetyl-L-serine + H2S ⇌ L-cysteine + acetate. [44]

EC 2.6: nitrogenous transferases Edit

The grouping consistent with transfer of nitrogenous groups is EC 2.6. This includes enzymes like transaminase (also known as "aminotransferase"), and a very small number of oximinotransferases and other nitrogen group transferring enzymes. EC 2.6 previously included amidinotransferase but it has since been reclassified as a subcategory of EC 2.1 (single-carbon transferring enzymes). [45] In the case of aspartate transaminase, which can act on tyrosine, phenylalanine, and tryptophan, it reversibly transfers an amino group from one molecule to the other. [46]

The reaction, for example, follows the following order: L-aspartate +2-oxoglutarate ⇌ oxaloacetate + L-glutamate. [47]

EC 2.7: phosphorus transferases Edit

While EC 2.7 includes enzymes that transfer phosphorus-containing groups, it also includes nuclotidyl transferases as well. [48] Sub-category phosphotransferase is divided up in categories based on the type of group that accepts the transfer. [24] Groups that are classified as phosphate acceptors include: alcohols, carboxy groups, nitrogenous groups, and phosphate groups. [29] Further constituents of this subclass of transferases are various kinases. A prominent kinase is cyclin-dependent kinase (or CDK), which comprises a sub-family of protein kinases. As their name implies, CDKs are heavily dependent on specific cyclin molecules for activation. [49] Once combined, the CDK-cyclin complex is capable of enacting its function within the cell cycle. [50]

The reaction catalyzed by CDK is as follows: ATP + a target protein → ADP + a phosphoprotein. [51]

EC 2.8: sulfur transferases Edit

Transfer of sulfur-containing groups is covered by EC 2.8 and is subdivided into the subcategories of sulfurtransferases, sulfotransferases, and CoA-transferases, as well as enzymes that transfer alkylthio groups. [53] A specific group of sulfotransferases are those that use PAPS as a sulfate group donor. [54] Within this group is alcohol sulfotransferase which has a broad targeting capacity. [55] Due to this, alcohol sulfotransferase is also known by several other names including "hydroxysteroid sulfotransferase," "steroid sulfokinase," and "estrogen sulfotransferase." [56] Decreases in its activity has been linked to human liver disease. [57] This transferase acts via the following reaction: 3'-phosphoadenylyl sulfate + an alcohol ⇌ adenosine 3',5'bisphosphate + an alkyl sulfate. [58]

EC 2.9: selenium transferases Edit

EC 2.9 includes enzymes that transfer selenium-containing groups. [59] This category only contains two transferases, and thus is one of the smallest categories of transferase. Selenocysteine synthase, which was first added to the classification system in 1999, converts seryl-tRNA(Sec UCA) into selenocysteyl-tRNA(Sec UCA). [60]

EC 2.10: metal transferases Edit

The category of EC 2.10 includes enzymes that transfer molybdenum or tungsten-containing groups. However, as of 2011, only one enzyme has been added: molybdopterin molybdotransferase. [61] This enzyme is a component of MoCo biosynthesis in Escherichia coli. [62] The reaction it catalyzes is as follows: adenylyl-molybdopterin + molybdate → molybdenum cofactor + AMP. [63]

The A and B transferases are the foundation of the human ABO blood group system. Both A and B transferases are glycosyltransferases, meaning they transfer a sugar molecule onto an H-antigen. [64] This allows H-antigen to synthesize the glycoprotein and glycolipid conjugates that are known as the A/B antigens. [64] The full name of A transferase is alpha 1-3-N-acetylgalactosaminyltransferase [65] and its function in the cell is to add N-acetylgalactosamine to H-antigen, creating A-antigen. [66] : 55 The full name of B transferase is alpha 1-3-galactosyltransferase, [65] and its function in the cell is to add a galactose molecule to H-antigen, creating B-antigen. [66]

It is possible for Homo sapiens to have any of four different blood types: Type A (express A antigens), Type B (express B antigens), Type AB (express both A and B antigens) and Type O (express neither A nor B antigens). [67] The gene for A and B transferases is located on chromosome 9. [68] The gene contains seven exons and six introns [69] and the gene itself is over 18kb long. [70] The alleles for A and B transferases are extremely similar. The resulting enzymes only differ in 4 amino acid residues. [66] The differing residues are located at positions 176, 235, 266, and 268 in the enzymes. [66] : 82–83

Transferase deficiencies are at the root of many common illnesses. The most common result of a transferase deficiency is a buildup of a cellular product.

SCOT deficiency Edit

Succinyl-CoA:3-ketoacid CoA transferase deficiency (or SCOT deficiency) leads to a buildup of ketones. [71] Ketones are created upon the breakdown of fats in the body and are an important energy source. [72] Inability to utilize ketones leads to intermittent ketoacidosis, which usually first manifests during infancy. [72] Disease sufferers experience nausea, vomiting, inability to feed, and breathing difficulties. [72] In extreme cases, ketoacidosis can lead to coma and death. [72] The deficiency is caused by mutation in the gene OXCT1. [73] Treatments mostly rely on controlling the diet of the patient. [74]

CPT-II deficiency Edit

Carnitine palmitoyltransferase II deficiency (also known as CPT-II deficiency) leads to an excess long chain fatty acids, as the body lacks the ability to transport fatty acids into the mitochondria to be processed as a fuel source. [75] The disease is caused by a defect in the gene CPT2. [76] This deficiency will present in patients in one of three ways: lethal neonatal, severe infantile hepatocardiomuscular, and myopathic form. [76] The myopathic is the least severe form of the deficiency and can manifest at any point in the lifespan of the patient. [76] The other two forms appear in infancy. [76] Common symptoms of the lethal neonatal form and the severe infantile forms are liver failure, heart problems, seizures and death. [76] The myopathic form is characterized by muscle pain and weakness following vigorous exercise. [76] Treatment generally includes dietary modifications and carnitine supplements. [76]

Galactosemia Edit

Galactosemia results from an inability to process galactose, a simple sugar. [77] This deficiency occurs when the gene for galactose-1-phosphate uridylyltransferase (GALT) has any number of mutations, leading to a deficiency in the amount of GALT produced. [78] [79] There are two forms of Galactosemia: classic and Duarte. [80] Duarte galactosemia is generally less severe than classic galactosemia and is caused by a deficiency of galactokinase. [81] Galactosemia renders infants unable to process the sugars in breast milk, which leads to vomiting and anorexia within days of birth. [81] Most symptoms of the disease are caused by a buildup of galactose-1-phosphate in the body. [81] Common symptoms include liver failure, sepsis, failure to grow, and mental impairment, among others. [82] Buildup of a second toxic substance, galactitol, occurs in the lenses of the eyes, causing cataracts. [83] Currently, the only available treatment is early diagnosis followed by adherence to a diet devoid of lactose, and prescription of antibiotics for infections that may develop. [84]

Choline acetyltransferase deficiencies Edit

Choline acetyltransferase (also known as ChAT or CAT) is an important enzyme which produces the neurotransmitter acetylcholine. [85] Acetylcholine is involved in many neuropsychic functions such as memory, attention, sleep and arousal. [86] [87] [88] The enzyme is globular in shape and consists of a single amino acid chain. [89] ChAT functions to transfer an acetyl group from acetyl co-enzyme A to choline in the synapses of nerve cells and exists in two forms: soluble and membrane bound. [89] The ChAT gene is located on chromosome 10. [90]

Alzheimer's disease Edit

Decreased expression of ChAT is one of the hallmarks of Alzheimer's disease. [91] Patients with Alzheimer's disease show a 30 to 90% reduction in activity in several regions of the brain, including the temporal lobe, the parietal lobe and the frontal lobe. [92] However, ChAT deficiency is not believed to be the main cause of this disease. [89]

Amyotrophic lateral sclerosis (ALS or Lou Gehrig's disease) Edit

Patients with ALS show a marked decrease in ChAT activity in motor neurons in the spinal cord and brain. [93] Low levels of ChAT activity are an early indication of the disease and are detectable long before motor neurons begin to die. This can even be detected before the patient is symptomatic. [94]

Huntington's disease Edit

Patients with Huntington's also show a marked decrease in ChAT production. [95] Though the specific cause of the reduced production is not clear, it is believed that the death of medium-sized motor neurons with spiny dendrites leads to the lower levels of ChAT production. [89]

Schizophrenia Edit

Patients with Schizophrenia also exhibit decreased levels of ChAT, localized to the mesopontine tegment of the brain [96] and the nucleus accumbens, [97] which is believed to correlate with the decreased cognitive functioning experienced by these patients. [89]

Sudden infant death syndrome (SIDS) Edit

Recent studies have shown that SIDS infants show decreased levels of ChAT in both the hypothalamus and the striatum. [89] SIDS infants also display fewer neurons capable of producing ChAT in the vagus system. [98] These defects in the medulla could lead to an inability to control essential autonomic functions such as the cardiovascular and respiratory systems. [98]

Congenital myasthenic syndrome (CMS) Edit

CMS is a family of diseases that are characterized by defects in neuromuscular transmission which leads to recurrent bouts of apnea (inability to breathe) that can be fatal. [99] ChAT deficiency is implicated in myasthenia syndromes where the transition problem occurs presynaptically. [100] These syndromes are characterized by the patients’ inability to resynthesize acetylcholine. [100]

Terminal transferases Edit

Terminal transferases are transferases that can be used to label DNA or to produce plasmid vectors. [101] It accomplishes both of these tasks by adding deoxynucleotides in the form of a template to the downstream end or 3' end of an existing DNA molecule. Terminal transferase is one of the few DNA polymerases that can function without an RNA primer. [101]

Glutathione transferases Edit

The family of glutathione transferases (GST) is extremely diverse, and therefore can be used for a number of biotechnological purposes. Plants use glutathione transferases as a means to segregate toxic metals from the rest of the cell. [102] These glutathione transferases can be used to create biosensors to detect contaminants such as herbicides and insecticides. [103] Glutathione transferases are also used in transgenic plants to increase resistance to both biotic and abiotic stress. [103] Glutathione transferases are currently being explored as targets for anti-cancer medications due to their role in drug resistance. [103] Further, glutathione transferase genes have been investigated due to their ability to prevent oxidative damage and have shown improved resistance in transgenic cultigens. [104]

Rubber transferases Edit

Currently the only available commercial source of natural rubber is the Hevea plant (Hevea brasiliensis). Natural rubber is superior to synthetic rubber in a number of commercial uses. [105] Efforts are being made to produce transgenic plants capable of synthesizing natural rubber, including tobacco and sunflower. [106] These efforts are focused on sequencing the subunits of the rubber transferase enzyme complex in order to transfect these genes into other plants. [106]

Many transferases associate with biological membranes as peripheral membrane proteins or anchored to membranes through a single transmembrane helix, [107] for example numerous glycosyltransferases in Golgi apparatus. Some others are multi-span transmembrane proteins, for example certain oligosaccharyltransferases or microsomal glutathione S-transferase from MAPEG family.


This dict comprehension works:

However, changing your data structure may be easier. You could have a dict of dicts:

Which allows each docs data to be directly accessed:

Or, just have a list of dicts with the position in the list corresponding to the doc index:

As others have mentioned, you could make this into a dictionary comprehension (python 2.7+):

But at this point I think that the comprehension is getting very difficult to comprehend (and therefore I wouldn't do it).

Also, someone should probably point out that if all your dictionary keys are sequential integers starting from 0 and going to 29, You probably shouldn't be using a dictionary to store this data -- maybe a list would be more appropriate .


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Because of sodomy laws and threat of prosecution due to the criminalization of homosexuality, LGBT slang has served as an argot or cant, a secret language and a way for the LGBT community to communicate with each other publicly without revealing their sexual orientation to others. [2] [3] [4] Since the advent of queer studies in universities, LGBT slang and argot has become a subject of academic research among linguistic anthropology scholars. [5]

During the first seven decades of the 20th century, a specific form of Polari was developed by gay men and lesbians in urban centres of the United Kingdom within established LGBT communities. Although there are differences, contemporary British gay slang has adopted many Polari words. [1] [6] The 1964 legislative report Homosexuality and Citizenship in Florida contains an extensive appendix documenting and defining the homosexual slang in the United States at that time. [7] [8] SCRUFF launched a gay-slang dictionary app in 2014, which includes commonly used slang in the United States from the gay community. [9] Specialized dictionaries that record LGBT slang have been found to revolve heavily around sexual matters. [10]

Slang is ephemeral. Terms used in one generation may pass out of usage in another. For example, in the 1960s and 1970s, the terms "cottage" (chiefly British) and "tearoom" (chiefly American) were used to denote public toilets used for sex. By 1999, this terminology had fallen out of use to the point of being greatly unrecognizable by members of the LGBT community at large. [11]

Many terms that originated as gay slang have become part of the popular lexicon. For example, the word drag was popularized by Hubert Selby Jr. in his book Last Exit to Brooklyn. Drag has been traced back by the Oxford English Dictionary (OED) to the late 19th Century. Conversely, words such as "banjee", while well-established in a subset of gay society, have never made the transition to popular use. Conversations between gay men have been found to use more slang and fewer commonly known terms about sexual behavior than conversations between straight men. [12]

[58]
Term Meaning Region References
100-footer an obviously gay or lesbian person (as if visible from 100 feet away) US [13]
AC/DC a slur towards bisexuals US [14]
ace short for someone who identifies on the asexual spectrum global [15]
aro short for someone who identifies on the aromantic spectrum global [16]
aroace,
aro-ace
short for someone who identifies as both aromantic and asexual global [16]
ace of spades someone who identifies as an aromantic asexual global [17]
ace of hearts someone who identifies as a romantic asexual global [17]
artiste a gay man who excels at fellatio US [18]
auntie an older, often effeminate and gossipy gay man US [18]
baby butch a young, boyish lesbian US [18]
baby dyke a young or recently out lesbian US [13]
baby gay a young or recently out gay person US
baths bathhouses frequented by gay men for sexual encounters US [18]
bathsheba a gay man who frequents gay bathhouses US [18]
batty boy a slur for gay or effeminate man Jamaica [19] [20]
beach bitch a gay man who frequents beaches and resorts for sexual encounters US [18]
bear a large, often hairy, gay man global [21] [22]
bear chaser a man who pursues bears US [22]
beard a person used as a date, romantic partner, or spouse to conceal one's sexual orientation global [23]
beat having or seeking anonymous gay sex Australia
bent gay, as opposed to straight US [18]
bicon an iconic bisexual+ individual US
bi-fi bisexual+ version of gaydar U.S.
boi a boyish lesbian UK [24]
bottom a passive male partner in anal intercourse also used as a verb for the state of receiving sexual stimulation global [18]
breeder a heterosexual person, especially one with children global [25]
brownie queen a gay man who prefers a passive role in anal intercourse US [18]
bucket boy a passive male partner in anal intercourse US [18]
bull dyke a mannish lesbian, as opposed to a baby butch or dinky dyke US [18]
butch a white masculine lesbian global [18] [26]
cafeteria repeated fellatio in a backroom or bathhouse US [18]
camp, campy effeminacy, effeminate global [18]
carpet muncher, rug muncher a lesbian/bisexual woman global [27]
Chicken Young gay man, usually recently out. Similar to twink global
Chicken Hawk Older gay man interested in young gay men (17-21) global
chubby chaser a man who seeks overweight males US [18]
clone a San Francisco or New York Greenwich Village denizen with exaggerated macho behavior and appearance US [18]
closeted keeping one's sexuality a secret from others US [18]
cocksucker a person who practices fellatio, usually a gay male US [18]
come out (of the closet) to admit or publicly acknowledge oneself as non-heterosexual/non-cisgender US [18]
Copenhagen capon a transsexual person (in reference to castration) US [18]
cottage a public toilet UK
cottaging having or seeking anonymous gay sex in a public toilet UK [21]
cotton ceiling lesbian refusal to have sex with a trans woman, particularly if the trans woman has not undergone sex reassignment surgery (a take-off on the term "glass ceiling", referring to women's underwear) global [28] [29] [30]
cruising seeking a casual gay sex encounter (historically from ancient Rome) global [18] [31]
cub a typically heavier, hairier, and younger gay man global [21] [22]
daddy a typically older gay man US [22]
down-low homosexual or bisexual activity, kept secret, by men who have sex with men US (African American) [32] [33] [34] [35]
dyke a slur reclaimed by any woman who is attracted to women in the 1950s global [31]
dykon a celebrity woman who is seen as an icon by lesbians may or may not be a lesbian herself US [13]
egg a (suspected, if referring to someone in the present) transgender person who has not realized they're trans yet. Used by transgender people when aspects of one's personality or behavior remind them of gender-related aspects of themselves before they realized they were trans. global
enby a non-binary person. the term derives from the abbreviation 'NB' US [36]
en femme, en homme the act of wearing clothes stereotypically of the opposite sex global [37]
fag, faggot a slur against gay men (first recorded in a Portland, Oregon, publication in 1914) global [31]
fag hag a woman who associates mostly or exclusively with gay and bisexual men US [38]
fairy a stereotypically gay man a slur reclaimed by gay men in the 1960s global [31]
femme a feminine homosexual US [13]
fish a drag queen who is effeminate enough to pass as a cis woman
flamer an effeminate gay man global [39]
friend of Dorothy a gay man US [40]
fruit a slur against gay men originally a stereotype of gay men as "softer" and "smelling good" global [31]
fudgepacker a gay man considered a slur global [41]
gaydar the intuitive ability of a person to guess someone's sexual orientation global
gaymer a gay gamer global
gaysian a gay Asian person global [42]
Gillette Blade a Bisexual+ feminine UK
gold star a homosexual who has never had heterosexual sexual intercourse US [13]
heteroflexible to be mostly heterosexual global [43]
homoflexible to be mostly gay global
horatian from the belated nineteenth century, term utilized at Oxford amongst Lord Byron along with his compatriots to a bisexual individuala bisexual+ masculine UK
lesbian until graduation (LUG) a woman who experiments with bisexual or homosexual activity during school only global [44]
lipstick lesbian a lesbian/bisexual woman who displays historically feminine attributes such as wearing make-up, dresses, and high heels global [45]
muff-diver a lesbian global [46] [47]
otter a thinner, hairier gay man US [22]
packing the act of wearing padding or a phallic object to present the appearance of a penis global [48]
passing the act of being perceived by others as a cis person of one's preferred gender identity global [49]
pillow princess a lesbian who prefers to receive sexual stimulation (to bottom) US [13]
poz a usually gay, HIV-positive person US [22]
punk a smaller, younger gay man who, in prison settings, is forced into a submissive role and used for the older inmate's sexual pleasure global [31]
queen an effeminate gay man commonly used in compounds such as "drag queen" or "rice queen" global [31]
queer originally a slur against homosexuals, transgender people, and anyone who does not fit society's standards of gender and sexuality recently reclaimed and used as umbrella term for sexual and gender minorities global [31]
soft butch, stem, stemme an androgynous lesbian, in between femme and butch US [13]
stone butch a very masculine lesbian, or a butch lesbian who does not receive touch during intercourse, only giving US [13]
stud a black masculine lesbian
swish effeminate or effeminacy US [50] [51]
terf "trans-exclusionary radical feminist", a transphobe one that targets trans women under the supposed guise of feminism. global [52] [53] [54] [55] [56] [57]
top the dominant or inserting sexual partner, usually in a homosexual relation or activity global [22]
twink a slim and young-looking, bodily hairless man global [21] [22]
unicorn a bisexual person who prefers to hook up with opposite sex couples US
vers, switch a person who enjoys both topping and bottoming, or being dominant and submissive, and may alternate between the two in sexual situations, adapting to their partner global
wolf a man who tends to fall evenly between a fox/twink or a bear/cub UK [21]
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T., Anna (2020). Opacity - Minority - Improvisation: An Exploration of the Closet Through Queer Slangs and Postcolonial Theory. Bielefeld: Transcript. ISBN 978-3-8376-5133-1.


Cell Biology

Microtubules periodically contract to force this excess water out of the cell, regulating the cell's osmotic balance.

cytoplasm -- All the contents of a cell, including the plasma membrane,but not including the nucleus.

cytoskeleton -- Integrated system of molecules within eukaryotic cells which provides them with shape, internal spatial organization, motility, and may assist in communication with other cells and the environment.

Microtubules periodically contract to force this excess water out of the cell, regulating the cell's osmotic balance.

cytoplasm -- All the contents of a cell, including the plasma membrane,but not including the nucleus.

cytoskeleton -- Integrated system of molecules within eukaryotic cells which provides them with shape, internal spatial organization, motility, and may assist in communication with other cells and the environment.

A dikaryotic individual is called a dikaryon.

diploid -- Having two different sets of chromosomes in the same nucleus of each cell.

Plants are known for their cell walls of cellulose, as are the green algae and certain protists, while fungi have cell walls of chitin.

chloroplast -- A chlorophyll-containing plastid found in algal and green plant cells.

chromosome -- Linear piece of eukaryotic DNA, often bound by specialized proteins known as histones.

coenocytic -- Condition in which an organism consists of filamentous cells with large central vacuoles, and whose nuclei are not partitioned into separate.

The cell consists primarily of an outer plasma membrane, which separates it from the environment the genetic material (DNA), which encodes heritable information for the maintainance of life and the cytoplasm, a heterogeneous assemblage of ions, molecules, and fluid.

cell cycle -- Complete sequence of steps which must be performed by a cell in order to replicate itself, as seen from mitotic event to mitotic event.

Plants are known for their cell walls of cellulose, as are the green algae and certain protists, while fungi have cell walls of chitin.

chloroplast -- A chlorophyll-containing plastid found in algal and green plant cells.

chromosome -- Linear piece of eukaryotic DNA, often bound by specialized proteins known as histones.

coenocytic -- Condition in which an organism consists of filamentous cells with large central vacuoles, and whose nuclei are not partitioned into separate.

Compare with haploid.

double membrane -- In mitochondria and plastids, there is a two-layered membrane which surrounds the organelle.

Plants are known for their cell walls of cellulose, as are the green algae and certain protists, while fungi have cell walls of chitin.

chloroplast -- A chlorophyll-containing plastid found in algal and green plant cells.

chromosome -- Linear piece of eukaryotic DNA, often bound by specialized proteins known as histones.

coenocytic -- Condition in which an organism consists of filamentous cells with large central vacuoles, and whose nuclei are not partitioned into separate.

For this reason, they have become essential tools of genetic engineers.

capsid -- The protein "shell" of a free virus particle.

cell -- Fundamental structural unit of all life.

Plants are known for their cell walls of cellulose, as are the green algae and certain protists, while fungi have cell walls of chitin.

chloroplast -- A chlorophyll-containing plastid found in algal and green plant cells.

chromosome -- Linear piece of eukaryotic DNA, often bound by specialized proteins known as histones.

coenocytic -- Condition in which an organism consists of filamentous cells with large central vacuoles, and whose nuclei are not partitioned into separate.

amoeboid -- Having no definite shape to the cell, able to change shape.

amphiesma -- The outer covering of a dinoflagellate, consisting of several membrane layers.

aperture -- Small opening, for example the opening in the test of a foram.

bacteriophage -- Virus which infects and destroys a bacterial host.

The cell consists primarily of an outer plasma membrane, which separates it from the environment the genetic material (DNA), which encodes heritable information for the maintainance of life and the cytoplasm, a heterogeneous assemblage of ions, molecules, and fluid.

cell cycle -- Complete sequence of steps which must be performed by a cell in order to replicate itself, as seen from mitotic event to mitotic event.

double membrane -- In mitochondria and plastids, there is a two-layered membrane which surrounds the organelle.

Plants are known for their cell walls of cellulose, as are the green algae and certain protists, while fungi have cell walls of chitin.

chloroplast -- A chlorophyll-containing plastid found in algal and green plant cells.

chromosome -- Linear piece of eukaryotic DNA, often bound by specialized proteins known as histones.

coenocytic -- Condition in which an organism consists of filamentous cells with large central vacuoles, and whose nuclei are not partitioned into separate.

Also called a plasma membrane or plasmalemma.

cell wall -- Rigid structure deposited outside the cell membrane.

Most of the cycle consists of a growth period in which the cell takes on mass and replicates its DNA. Arrest of the cell cycle is an important feature in the reproduction of many organisms, including humans.

cell membrane -- The outer membrane of a cell, which separates it from the environment.

amoeboid -- Having no definite shape to the cell, able to change shape.

amphiesma -- The outer covering of a dinoflagellate, consisting of several membrane layers.

aperture -- Small opening, for example the opening in the test of a foram.

bacteriophage -- Virus which infects and destroys a bacterial host.

Plants are known for their cell walls of cellulose, as are the green algae and certain protists, while fungi have cell walls of chitin.

chloroplast -- A chlorophyll-containing plastid found in algal and green plant cells.

chromosome -- Linear piece of eukaryotic DNA, often bound by specialized proteins known as histones.

coenocytic -- Condition in which an organism consists of filamentous cells with large central vacuoles, and whose nuclei are not partitioned into separate.

Plants are known for their cell walls of cellulose, as are the green algae and certain protists, while fungi have cell walls of chitin.

chloroplast -- A chlorophyll-containing plastid found in algal and green plant cells.

chromosome -- Linear piece of eukaryotic DNA, often bound by specialized proteins known as histones.

coenocytic -- Condition in which an organism consists of filamentous cells with large central vacuoles, and whose nuclei are not partitioned into separate.

Plants are known for their cell walls of cellulose, as are the green algae and certain protists, while fungi have cell walls of chitin.

chloroplast -- A chlorophyll-containing plastid found in algal and green plant cells.

chromosome -- Linear piece of eukaryotic DNA, often bound by specialized proteins known as histones.

coenocytic -- Condition in which an organism consists of filamentous cells with large central vacuoles, and whose nuclei are not partitioned into separate.

Microtubules periodically contract to force this excess water out of the cell, regulating the cell's osmotic balance.

cytoplasm -- All the contents of a cell, including the plasma membrane,but not including the nucleus.

cytoskeleton -- Integrated system of molecules within eukaryotic cells which provides them with shape, internal spatial organization, motility, and may assist in communication with other cells and the environment.

amoeboid -- Having no definite shape to the cell, able to change shape.

amphiesma -- The outer covering of a dinoflagellate, consisting of several membrane layers.

aperture -- Small opening, for example the opening in the test of a foram.

bacteriophage -- Virus which infects and destroys a bacterial host.

Plants are known for their cell walls of cellulose, as are the green algae and certain protists, while fungi have cell walls of chitin.

chloroplast -- A chlorophyll-containing plastid found in algal and green plant cells.

chromosome -- Linear piece of eukaryotic DNA, often bound by specialized proteins known as histones.

coenocytic -- Condition in which an organism consists of filamentous cells with large central vacuoles, and whose nuclei are not partitioned into separate.

Microtubules periodically contract to force this excess water out of the cell, regulating the cell's osmotic balance.

cytoplasm -- All the contents of a cell, including the plasma membrane,but not including the nucleus.

cytoskeleton -- Integrated system of molecules within eukaryotic cells which provides them with shape, internal spatial organization, motility, and may assist in communication with other cells and the environment.

amoeboid -- Having no definite shape to the cell, able to change shape.

amphiesma -- The outer covering of a dinoflagellate, consisting of several membrane layers.

aperture -- Small opening, for example the opening in the test of a foram.

bacteriophage -- Virus which infects and destroys a bacterial host.

Unlike true multicellular organisms, the individual cells retain their separate identities, and usually, their own membranes and cell walls.

contractile vacuole -- In many protists, a specialized vacuole with associated channels designed to collect excess water in the cell.

double membrane -- In mitochondria and plastids, there is a two-layered membrane which surrounds the organelle.


Contents

The word diazotroph is derived from the words diazo ("di" = two + "azo" = nitrogen) meaning "dinitrogen (N2)" and troph meaning "pertaining to food or nourishment", in summary dinitrogen utilizing. The word azote means nitrogen in French and was named by French chemist and biologist Antoine Lavoisier, who saw it as the part of air which cannot sustain life. [14]

Diazotrophs are scattered across Bacteria taxonomic groups (as well as a couple of Archaea). Even within a species that can fix nitrogen there may be strains that do not. [15] Fixation is shut off when other sources of nitrogen are available, and, for many species, when oxygen is at high partial pressure. Bacteria have different ways of dealing with the debilitating effects of oxygen on nitrogenases, listed below.

Free-living diazotrophs Edit

  • Anaerobes—these are obligate anaerobes that cannot tolerate oxygen even if they are not fixing nitrogen. They live in habitats low in oxygen, such as soils and decaying vegetable matter. Clostridium is an example. Sulphate-reducing bacteria are important in ocean sediments (e.g. Desulfovibrio), and some Archean methanogens, like Methanococcus, fix nitrogen in muds, animal intestines [15] and anoxic soils. [16]
  • Facultative anaerobes—these species can grow either with or without oxygen, but they only fix nitrogen anaerobically. Often, they respire oxygen as rapidly as it is supplied, keeping the amount of free oxygen low. Examples include Klebsiella pneumoniae, Paenibacillus polymyxa, Bacillus macerans, and Escherichia intermedia. [15]
  • Aerobes—these species require oxygen to grow, yet their nitrogenase is still debilitated if exposed to oxygen. Azotobacter vinelandii is the most studied of these organisms. It uses very high respiration rates, and protective compounds, to prevent oxygen damage. Many other species also reduce the oxygen levels in this way, but with lower respiration rates and lower oxygen tolerance. [15]
  • Oxygenic photosynthetic bacteria (cyanobacteria) generate oxygen as a by-product of photosynthesis, yet some are able to fix nitrogen as well. These are colonial bacteria that have specialized cells (heterocysts) that lack the oxygen generating steps of photosynthesis. Examples are Anabaena cylindrica and Nostoc commune. Other cyanobacteria lack heterocysts and can fix nitrogen only in low light and oxygen levels (e.g. Plectonema). [15] Some cyanobacteria, including the highly abundant marine taxa Prochlorococcus and Synechococcus do not fix nitrogen, [17] whilst other marine cyanobacteria, such as Trichodesmium and Cyanothece, are major contributors to oceanic nitrogen fixation. [18]
  • Anoxygenic photosynthetic bacteria do not generate oxygen during photosynthesis, having only a single photosystem which cannot split water. Nitrogenase is expressed under nitrogen limitation. Normally, the expression is regulated via negative feedback from the produced ammonium ion but in the absence of N2, the product is not formed, and the by-product H2 continues unabated [Biohydrogen]. Example species: Rhodobacter sphaeroides, Rhodopseudomonas palustris, Rhodobacter capsulatus. [19]

Symbiotic diazotrophs Edit

    —these are the species that associate with legumes, plants of the family Fabaceae. Oxygen is bound to leghemoglobin in the root nodules that house the bacterial symbionts, and supplied at a rate that will not harm the nitrogenase. [15] —much less is known about these 'actinorhizal' nitrogen fixers. The bacteria also infect the roots leading to the formation of nodules. Actinorhizal nodules consist of several lobes, each lobe has a similar structure as a lateral root. Frankia is able to colonize in the cortical tissue of nodules where it fixes nitrogen. [20] Actinorhizal plants and Frankias also produce haemoglobins, [21] but their role is less well established than for rhizobia. [20] Although at first it appeared that they inhabit sets of unrelated plants (alders, Australian pines, California lilac, bog myrtle, bitterbrush, Dryas), revisions to the phylogeny of angiosperms show a close relatedness of these species and the legumes. [22][20] These footnotes suggest the ontogeny of these replicates rather than the phylogeny. In other words, an ancient gene (from before the angiosperms and gymnosperms diverged) that is unused in most species was reawakened and reused in these species. —there are also symbiotic cyanobacteria. Some associate with fungi as lichens, with liverworts, with a fern, and with a cycad. [15] These do not form nodules (indeed most of the plants do not have roots). Heterocysts exclude the oxygen, as discussed above. The fern association is important agriculturally: the water fern Azolla harbouring Anabaena is an important green manure for rice culture. [15]
  • Association with animals—although diazotrophs have been found in many animal guts, there is usually sufficient ammonia present to suppress nitrogen fixation. [15]Termites on a low nitrogen diet allow for some fixation, but the contribution to the termite's nitrogen supply is negligible. Shipworms may be the only species that derive significant benefit from their gut symbionts. [15]

In terms of generating nitrogen available to all organisms, the symbiotic associations greatly exceed the free-living species with the exception of cyanobacteria. [15]


Watch the video: Notes for IB Biology Chapter (September 2022).


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