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2017 Sugar Bowl
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2017 Allstate Sugar Bowl
CFP Bowl Game
83rd Allstate Sugar Bowl
Auburn Tigers Oklahoma Sooners
(8–4) (10–2)
SEC Big 12
19 35
Head coach:
Gus Malzahn Head coach:
Bob Stoops
AP Coaches CFP
17 17 14
AP Coaches CFP
7 7 7
1
2
3
4
Total
Auburn 7 6 0 6 19
Oklahoma 0 14 14 7 35
Date
January 2, 2017
Season
2016
Stadium
Mercedes-Benz Superdome
Location
New Orleans, Louisiana
Favorite
Oklahoma by 3[1]
Referee
John O'Neill (Big Ten)[2]
Attendance
54,077
United States TV coverage
Network
ESPN
Announcers
Brent Musburger (play-by-play)
Jesse Palmer (analyst)
Kaylee Hartung (sideline reporter)
Sugar Bowl
< 2016 2018 >
The 2017 Sugar Bowl is a bowl game that was played on January 2, 2017 at the Mercedes-Benz Superdome in New Orleans, Louisiana. This 83rd Sugar Bowl was played between a team from the Big 12 Conference and the Southeastern Conference. It is one of the 2016–17 bowl games that concluded the 2016 FBS football season. Sponsored by the Allstate insurance company, the game is officially known as the Allstate Sugar Bowl.
Contents
[hide]
1 Teams
1.1 Auburn
1.2 Oklahoma
2 Game summary
2.1 Scoring summary
2.2 Statistics
3 References
Teams[edit]
The two teams were selected by the College Football Playoff committee on December 4, 2016. The highest-ranked team from the SEC and the Big 12 were to be selected. However, the highest-ranked team from the SEC, Alabama, was selected in the semifinals of the playoff, so the second highest ranked SEC team went in their place. Auburn was the second highest ranked team at 14th in the playoff rankings, so they were selected for the Sugar Bowl. Oklahoma was the Big 12 champion and the conference's highest ranked at 7th, therefore sending the Sooners to the Sugar Bowl.
This was the second meeting between the two schools; the previous meeting was the 1972 Sugar Bowl, which saw the Sooners defeat the Tigers by a score of 40–22.
Auburn[edit]
After a disappointing 2015 season, Auburn coach Gus Malzahn was considered to be at risk of losing his job if a similar season followed. The season started out poorly for the Tigers, as they started 1–2, with both losses coming to nationally-ranked teams. However, in week 4, the Tigers played rival LSU. LSU was #18 heading into the game, but it was Auburn that won 18–13. That started a six-game win streak that put the Tigers into the national Top 10. Towards the end of the season, injuries began to plague the Tigers, and they lost 2 of their final 3 games. However, losses by Tennessee and Florida sent the Tigers to the Sugar Bowl.
Oklahoma[edit]
Oklahoma made the playoff in the 2015 season, and many experts expected them to compete for another playoff berth. However, much like Auburn, the Sooners started 1–2, with both losses coming against nationally-ranked opponents. That start ended any hope of going back to the playoff. In the annual rivalry game against Texas, the Sooners won a close and hard-fought victory over the Longhorns, which started a turnaround and a nine-game win streak for the Sooners. Included in that win streak was a win against Oklahoma State which gave the Sooners the Big 12 championship and the Sugar Bowl berth.
Game summary[edit]
Scoring summary[edit]
[hide]Scoring summary
Quarter
Time
Drive
Team
Scoring information
Score
Plays
Yards
TOP
AUB
OKLA
1 9:04 14 75 5:56 AUB Chandler Cox 3-yard touchdown run, Daniel Carlson kick good 7 0
2 11:24 14 90 6:39 OKLA Mark Andrews 13-yard touchdown reception from Baker Mayfield, Austin Seibert kick good 7 7
2 7:16 12 43 4:08 AUB 49-yard field goal by Daniel Carlson 10 7
2 3:37 9 75 3:39 OKLA Joe Mixon 3-yard touchdown run, Austin Seibert kick good 10 14
2 0:41 11 63 2:56 AUB 39-yard field goal by Daniel Carlson 13 14
3 12:39 6 75 2:21 OKLA Dede Westbrook 7-yard touchdown reception from Baker Mayfield, Austin Seibert kick good 13 21
3 2:28 7 85 3:02 OKLA Joe Mixon 4-yard touchdown run, Austin Seibert kick good 13 28
4 12:40 8 71 3:57 OKLA Samaje Perine 2-yard touchdown run, Austin Seibert kick good 13 35
4 0:00 10 91 2:30 AUB Jalen Harris 1-yard touchdown reception from Kerryon Johson, no conversion attempted / kick noneβ 19 35
"TOP" = time of possession. For other American football terms, see Glossary of American football.
19
35
^β NCAA rules state "the try shall not be attempted unless the point(s) would affect the outcome of the game."[3]
Statistics[edit]
Statistics
Auburn
Oklahoma
First Downs 30 36
Plays-yards 73/339 71/524
Third down efficiency 5/15 5/10
Rushes-yards 185 228
Passing yards 154 296
Passing, Comp-Att-Int 13/27, 1 int. 19/28, 0 int.
Time of Possession 26:42 33:18
Team
Category
Player
Statistics
Auburn Passing Sean White 4/10, 35 yards, 0 TD, 0 int., QB rating = 69.4
Rushing Kamryn Pettway 24/101 yards, 0 TD
Receiving Eli Stove 4/39 yards, 0 TD
Oklahoma Passing Baker Mayfield 19/28, 296 yards, 2 TD, 0 int., QB rating = 180.2
Rushing Joe Mixon 19/91 yards, 2 TD
Receiving Dede Westbrook 6/59 yards, 1 TD
References[edit]
Jump up ^ "Sports Betting News and Vegas Odds". Archived from the original on 27 December 2011. Retrieved 2 January 2017.
Jump up ^ http://stats.statbroadcast.com/statmonitr/?id=155858
Jump up ^ http://newsok.com/article/3788492
[show]
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2016–17 NCAA football bowl game season
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Cure (Dec. 17)
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College Football Playoff games: Peach (semifinal) (Dec. 31)
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National Championship Game (Jan. 9)
All-Star Games: 2017 East–West Shrine Game (Jan. 21)
NFLPA Collegiate Bowl (Jan. 21)
Senior Bowl (Jan. 28)
[show]
v
t
e
Sugar Bowl Game
History & conference tie-ins
History
Tulane Stadium
Georgia Dome
Mercedes-Benz Superdome
College Football Playoff
Broadcasters
Southeastern Conference
Big 12 Conference
Games
1935
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
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1954
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2005
2006
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2013
2014
2015
2016
2017
2018
Notes
The 2006 game took place in Atlanta, Georgia due to Hurricane Katrina.
The game was also the national title game for either the Bowl Coalition, Bowl Alliance, or Bowl Championship Series in 1993, 1997, 2000, and 2004.
There was a Sugar Bowl in January and December in 1972 and 1995.
The game was a College Football Playoff semifinal in its 2015 and 2018 editions.
[show]
v
t
e
Auburn Tigers bowl games
1937 Bacardi Bowl
1938 Orange Bowl
1954 Gator Bowl
1954 Gator Bowl
1955 Gator Bowl
1964 Orange Bowl
1965 Liberty Bowl
1968 Sun Bowl
1969 Astro-Bluebonnet Bowl
1971 Gator Bowl
1972 Sugar Bowl
1972 Gator Bowl
1973 Sun Bowl
1974 Gator Bowl
1982 Tangerine Bowl
1984 Sugar Bowl
1984 Liberty Bowl
1986 Cotton Bowl Classic
1987 Florida Citrus Bowl
1988 Sugar Bowl
1989 Sugar Bowl
1990 Hall of Fame Bowl
1990 Peach Bowl
1996 Outback Bowl
1996 Independence Bowl
1998 Peach Bowl
2001 Florida Citrus Bowl
2001 Peach Bowl
2003 Capital One Bowl
2003 Music City Bowl
2005 Sugar Bowl
2006 Capital One Bowl
2007 Cotton Bowl Classic
2007 Chick-fil-A Bowl
2010 Outback Bowl
2011 BCS National Championship Game #
2011 Chick-fil-A Bowl
2014 BCS National Championship Game #
2015 Outback Bowl
2015 Birmingham Bowl
2017 Sugar Bowl
2018 Peach Bowl
Pound sign (#) denotes national championship game.
[show]
v
t
e
Oklahoma Sooners bowl games
1939 Orange Bowl
1947 Gator Bowl
1949 Sugar Bowl
1950 Sugar Bowl
1951 Sugar Bowl
1954 Orange Bowl
1956 Orange Bowl
1958 Orange Bowl
1959 Orange Bowl
1963 Orange Bowl
1965 Gator Bowl
1968 Orange Bowl
1968 Astro-Bluebonnet Bowl
1970 Astro-Bluebonnet Bowl
1972 Sugar Bowl (January)
1972 Sugar Bowl (December)
1976 Orange Bowl
1976 Fiesta Bowl
1978 Orange Bowl
1979 Orange Bowl
1980 Orange Bowl
1981 Orange Bowl
1981 Sun Bowl
1983 Fiesta Bowl
1985 Orange Bowl
1986 Orange Bowl
1987 Orange Bowl
1988 Orange Bowl
1989 Florida Citrus Bowl
1991 Gator Bowl
1993 John Hancock Bowl
1994 Copper Bowl
1999 Independence Bowl
2001 Orange Bowl #
2002 Cotton Bowl Classic
2003 Rose Bowl
2004 Sugar Bowl #
2005 Orange Bowl #
2005 Holiday Bowl
2007 Fiesta Bowl
2008 Fiesta Bowl
2009 BCS National Championship Game #
2009 Sun Bowl
2011 Fiesta Bowl
2011 Insight Bowl
2013 Cotton Bowl Classic
2014 Sugar Bowl
2014 Russell Athletic Bowl
2015 Orange Bowl /
2017 Sugar Bowl
2018 Rose Bowl /
Pound sign (#) denotes national championship game. Forward slash (/) denotes College Football Playoff semifinal game
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Quorum sensing
From Wikipedia, the free encyclopedia
Jump to: navigation, search
In biology, quorum sensing is a system of stimuli and response correlated to population density. As one example, quorum sensing (QS) enables bacteria to restrict the expression of specific genes to the high cell densities at which the resulting phenotypes will be most beneficial. Many species of bacteria use quorum sensing to coordinate gene expression according to the density of their local population. In similar fashion, some social insects use quorum sensing to determine where to nest.
In addition to its function in biological systems, quorum sensing has several useful applications for computing and robotics. In general, quorum sensing can function as a decision-making process in any decentralized system in which the components have: (a) a means of assessing the number of other components they interact with and (b) a standard response once a threshold number of components is detected.
Contents
[hide]
1 Bacteria
1.1 Mechanism
1.1.1 Gram-positive Bacteria
1.1.2 Gram-negative Bacteria
1.2 Examples
1.2.1 Aliivibrio fischeri
1.2.2 Escherichia coli
1.2.3 Salmonella enterica
1.2.4 Pseudomonas aeruginosa
1.2.5 Acinetobacter sp.
1.2.6 Aeromonas sp.
1.2.7 Yersinia
1.3 Molecules involved in quorum sensing
1.4 Evolution
1.4.1 Sequence analysis
1.4.2 Controversy
1.4.3 Interaction of quorum-sensing molecules with mammalian cells and its medical applications
2 Archaea
2.1 Examples
2.1.1 Methanosaeta harundinacea 6Ac
3 Plants
4 Quorum quenching
5 Social insects
5.1 Examples
5.1.1 Ants
5.1.2 Honey bees
6 Computing and robotics
7 See also
8 References
9 Further reading
10 External links
Bacteria[edit]
Some of the best-known examples of quorum sensing come from studies of bacteria. Bacteria use quorum sensing to regulate certain phenotype expressions, which in turn, coordinate their behaviours. Some common phenotypes include biofilm formation, virulence factor expression, and motility. Certain bacteria are able to use quorum sensing to regulate bioluminescence, nitrogen fixation and sporulation. [1]
Quorum sensing functions based on the local density of the bacterial population in the immediate environment. [2] It can occur within a single bacterial species, as well as between diverse species. Both Gram-positive and gram-negative bacteria use quorum sensing, but there are some major differences in their mechanisms.[3]
Mechanism[edit]
In order for the bacteria to use quorum sensing constitutively, they must possess three characteristics: to secrete a signaling molecule, an autoinducer, to detect the change in concentration of signaling molecules, and to regulate gene transcription as a response. [1] This process is highly dependent on the diffusion mechanism of the signaling molecules. Signaling molecules are usually constitutively secreted at a low level by individual bacteria. At low cell density, the molecules may just diffuse away. At high cell density, the local concentration of signaling molecules may exceed its threshold level, and trigger changes in gene expressions.[3]
Gram-positive Bacteria[edit]
Gram-positive bacteria use autoinducing peptide (AIP) as their autoinducers. [4]
When gram-positive bacteria detect high concentration of AIP in the environment, AIP bind to a receptor to activate kinase. The kinase phosphorylates a transcription factor, which regulated gene transcription. This is called a two-component system.
Another possible mechanism is that AIP is transported into the cytosol, and binds directly to a transcription factor to initiate or inhibit transcription.[4]
Gram-negative Bacteria[edit]
Gram-negative bacteria produce N-acyl homoserine lactones (AHL) as their signaling molecule.[4] Usually AHLs do not need additional processing, and bind directly to transcription factors to regulate gene expression. [3]
Some gram-negative bacteria may use the two-component system as well. [4]
Quorum sensing of Gram Negative cell
Examples[edit]
Aliivibrio fischeri[edit]
Quorum sensing was first observed in Aliivibrio fischeri, a bioluminescent bacterium that lives as a mutualistic symbiont in the photophore (or light-producing organ) of the Hawaiian bobtail squid.[5] When A. fischeri cells are free-living (or planktonic), the autoinducer is at low concentration, and, thus, cells do not luminesce. However, when they are highly concentrated in the photophore (about 1011 cells/ml), transcription of luciferase is induced, leading to bioluminescence.
Escherichia coli[edit]
In the Gram-negative bacterium Escherichia coli (E. coli), cell division may be partially regulated by AI-2-mediated quorum sensing. This species uses AI-2, which is produced and processed by the lsr operon. Part of it encodes an ABC transporter, which imports AI-2 into the cells during the early stationary (latent) phase of growth. AI-2 is then phosphorylated by the LsrK kinase, and the newly produced phospho-AI-2 can be either internalized or used to suppress LsrR, a repressor of the lsr operon (thereby activating the operon). Transcription of the lsr operon is also thought to be inhibited by dihydroxyacetone phosphate (DHAP) through its competitive binding to LsrR. Glyceraldehyde 3-phosphate has also been shown to inhibit the lsr operon through cAMP-CAPK-mediated inhibition. This explains why, when grown with glucose, E. coli will lose the ability to internalize AI-2 (because of catabolite repression). When grown normally, AI-2 presence is transient.
E. coli and Salmonella enterica do not produce AHL signals commonly found in other Gram-negative bacteria. However, they have a receptor that detects AHLs from other bacteria and change their gene expression in accordance with the presence of other "quorate" populations of Gram-negative bacteria.[6]
Gram positive bacteria quorum sensing
Salmonella enterica[edit]
Salmonella encodes a LuxR homolog, SdiA, but does not encode an AHL synthase. SdiA detects AHLs produced by other species of bacteria including Aeromonas hydrophila, Hafnia alvei, and Yersinia enterocolitica.[7] When AHL is detected, SdiA regulates the rck operon on the Salmonella virulence plasmid (pefI-srgD-srgA-srgB-rck-srgC) and a single gene horizontal acquisition in the chromosome srgE.[8][9] Salmonella does not detect AHL when passing through the gastrointestinal tracts of several animal species, suggesting that the normal microbiota does not produce AHLs. However, SdiA does become activated when Salmonella transits through turtles colonized with Aeromonas hydrophila or mice infected with Yersinia enterocolitica.[10][11] Therefore, Salmonella appears to use SdiA to detect the AHL production of other pathogens rather than the normal gut flora.
Pseudomonas aeruginosa[edit]
The opportunistic pathogen Pseudomonas aeruginosa uses quorum sensing to coordinate the formation of biofilms, swarming motility, exopolysaccharide production, virulence, and cell aggregation.[12] These bacteria can grow within a host without harming it, until they reach a threshold concentration. Then they become aggressive, developing to the point at which their numbers are sufficient to overcome the host's immune system, and form a biofilm, leading to disease within the host as the biofilm is a protective layer encasing the bacteria population. Another form of gene regulation that allows the bacteria to rapidly adapt to surrounding changes is through environmental signaling. Recent studies have discovered that anaerobiosis can significantly impact the major regulatory circuit of quorum sensing. This important link between quorum sensing and anaerobiosis has a significant impact on production of virulence factors of this organism.[13] Garlic and ginseng experimentally block quorum sensing in Pseudomonas aeruginosa.[14] It is hoped that the therapeutic enzymatic degradation of the signaling molecules will prevent the formation of such biofilms and possibly weaken established biofilms. Disrupting the signalling process in this way is called quorum sensing inhibition.
Acinetobacter sp.[edit]
It has recently been found that Acinetobacter sp. also show quorum sensing activity. This bacterium, an emerging pathogen, produces AHLs.[15] Interestingly, Acinetobacter sp. shows both quorum sensing and quorum quenching activity. It produces AHLs and also, it can degrade the AHL molecules as well.[15]
Aeromonas sp.[edit]
This bacterium was previously considered a fish pathogen, but it has recently emerged as a human pathogen.[16] Aeromonas sp. have been isolated from various infected sites from patients (bile, blood, peritoneal fluid, pus, stool and urine). All isolates produced the two principal AHLs, N-butanoylhomoserine lactone (C4-HSL) and N-hexanoyl homoserine lactone (C6-HSL). It has been documented that Aeromonas sobria has produced C6-HSL and two additional AHLs with N-acyl side chain longer than C6.[17]
Yersinia [edit]
The YenR and YenI proteins produced by the gammaproteobacterium Yersinia enterocolitica are similar to Aliivibrio fischeri LuxR and LuxI.[18][19] YenR activates the expression of a small non-coding RNA, YenS. YenS inhibits YenI expression and acylhomoserine lactone production.[20] YenR/YenI/YenS are involved in the control of swimming and swarming motility.[19][20]
Molecules involved in quorum sensing[edit]
Three-dimensional structures of proteins involved in quorum sensing were first published in 2001, when the crystal structures of three LuxS orthologs were determined by X-ray crystallography.[21] In 2002, the crystal structure of the receptor LuxP of Vibrio harveyi with its inducer AI-2 (which is one of the few biomolecules containing boron) bound to it was also determined.[22] Many bacterial species, including E. coli, an enteric bacterium and model organism for Gram-negative bacteria, produce AI-2. A comparative genomic and phylogenetic analysis of 138 genomes of bacteria, archaea, and eukaryotes found that "the LuxS enzyme required for AI-2 synthesis is widespread in bacteria, while the periplasmic binding protein LuxP is present only in Vibrio strains," leading to the conclusion that either "other organisms may use components different from the AI-2 signal transduction system of Vibrio strains to sense the signal of AI-2 or they do not have such a quorum sensing system at all."[23] Farnesol is used by the fungus Candida albicans as a quorum sensing molecule that inhibits filamentation.[24]
A database of quorum-sensing peptides is available under the name Quorumpeps.[25][26]
Certain bacteria can produce enzymes called lactonases that can target and inactivate AHLs. Researchers have developed novel molecules which block the signalling receptors of bacteria. mBTL is a compound that has been shown to inhibit quorum sensing and decrease the amount of cell death by a significant amount.[27] Additionally, researchers are also examining the role of natural compounds (such as caffeine) as potential quorum sensing inhibitors.[28] Research in this area has been promising and could lead to the development of natural compounds as effective therapeutics.
Evolution[edit]
Sequence analysis[edit]
The majority of quorum sensing systems that fall under the "two-gene" (an autoinducer synthase coupled with a receptor molecule) paradigm as defined by the Vibrio fischeri system occur in the Gram-negative Proteobacteria. A comparison between the Proteobacteria phylogeny as generated by 16S ribosomal RNA sequences and phylogenies of LuxI-, LuxR-, or LuxS-homologs shows a notably high level of global similarity. Overall, the quorum sensing genes seem to have diverged along with the Proteobacteria phylum as a whole. This indicates that these quorum sensing systems are quite ancient, and arose very early in the Proteobacteria lineage.[29][30]
Although examples of horizontal gene transfer are apparent in LuxI, LuxR, and LuxS phylogenies, they are relatively rare. This result is in line with the observation that quorum sensing genes tend to control the expression of a wide array of genes scattered throughout the bacterial chromosome. A recent acquisition by horizontal gene transfer would be unlikely to have integrated itself to this degree. Given that the majority of autoinducer–synthase/receptor occurs in tandem in bacterial genomes, it is also rare that they switch partners and so pairs tend to co-evolve.[30]
The phylogeny of quorum sensing genes in Gammaproteobacteria (which includes Pseudomonas aeruginosa and Escherichia coli) is especially interesting.[according to whom?] The LuxI/LuxR genes form a functional pair, with LuxI as the auto-inducer synthase and LuxR as the receptor. Gamma Proteobacteria are unique in possessing quorum sensing genes, which, although functionally similar to the LuxI/LuxR genes, have a markedly divergent sequence.[30] This family of quorum-sensing homologs may have arisen in the gamma Proteobacteria ancestor, although the cause of their extreme sequence divergence yet maintenance of functional similarity has yet to be explained. In addition, species that employ multiple discrete quorum sensing systems are almost all members of the gamma Proteobacteria, and evidence of horizontal transfer of quorum sensing genes is most evident in this class.[29][30]
Controversy[edit]
As quorum sensing implies a cooperative behavior, this concept has been challenged by the evolutionary implication of cooperative cheaters. This is circumvented by the concept of diffusion sensing, which has been an alternative and complementary model to quorum sensing.[31] However, both explanations face the problems of signalling in either complex (multiple species sharing the same space) or simple (one single cell confined to a limited volume) environments where the spatial distribution of the cells can be more important for sensing than the cell population density. A new model, efficiency sensing, which takes into account both problematics, population density and spatial confinement, has been proposed as an alternative.[32] One of the probable reasons for controversy is that current terminologies (quorum sensing, diffusion sensing, efficiency sensing) arise from different models of how natural selection has acted to shape and maintain the process. Since each of the various models does apply under some circumstances but not others, a sensible resolution to these controversies could be to return the terminology of the process to autoinduction, as originally described by Hastings and coworkers, as this term does not imply understanding of the function of the process.
Interaction of quorum-sensing molecules with mammalian cells and its medical applications[edit]
Next to the potential antimicrobial functionality, quorum-sensing derived molecules, especially the peptides, are being investigated for their use in other therapeutic domains as well, including immunology, central nervous system disorders and oncology. Quorum-sensing peptides have been demonstrated to interact with cancer cells, as well as to permeate the blood-brain barrier permeation reaching the brain parenchyma[33][34][35][36]
Archaea[edit]
Examples[edit]
Methanosaeta harundinacea 6Ac[edit]
Methanosaeta harundinacea 6Ac, a methanogenic archaeon, produces carboxylated acyl homoserine lactone compounds that facilitate the transition from growth as short cells to growth as filaments.[37]
Plants[edit]
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Quorum sensing was described when it was known that bacteria possess the ability to communicate. Hence, in the last few years, there are interactions shown between bacteria and eukaryotic hosts, like plants. These interactions are carried in presence of quorum sensing molecules which play a major role in maintaining the pathogenicity of bacteria towards other hosts like humans. This mechanism can be understood by looking at the effects of N-acyl Homoserine Lactone (AHL) which is one of the quorum sensing-signalling molecules in Gram-negative bacteria, on plants.The model organism used is Arabidopsis thaliana.[38]
The role of AHLs having long Carbon chain (C12, C14) have an unknown mechanism and short Carbon chain (C4, C6, C8) was understood by G-protein Coupled Receptor. A phenomenon called AHL Priming which is a dependent signalling pathway enhanced the knowledge for long chain AHLs. The role of quorum sensing molecules was better explained with three categories: host physiology based impact of quorum sensing molecules; ecological effects; and cellular signaling. Calcium Signalling and Calmodulin has a great role in Short Chain AHLs response to Arabidopsis. Research was also conducted on Barley, Crop yam bean which reveals the AHLs determining the detoxification enzymes called GST which was found less in yam bean.[39]
Looking towards developing new strategies based on plant-associated microbiomes it is aimed to improve the food supply and quality. It opens more new opportunity to learn about the inter-kingdom communication explaining quorum sensing in humans. Quorum sensing-based regulatory systems are necessary to maintain plant diseases caused due to bacteria.[40]
Quorum quenching[edit]
Quorum quenching is the process of preventing quorum sensing by disrupting signalling.[41] This is achieved by inactivating signalling enzymes, by introducing molecules that mimic signalling molecules and block their receptors, or by degrading signalling molecules themselves.[41][42][43]
Closantel and triclosan are known inhibitors of quorum sensing enzymes.[44] Closantel induces aggregation of the histamine kinase sensor in two-component signalling. The latter disrupts the synthesis of a class of signalling molecules known as N-acyl homoserine lactones (AHLs) by blocking the enoyl-acyl carrier protein (ACP) reductase.[44][45]
Two groups of well-known mimicking molecules include halogenated furanones, which mimic AHL molecules, and synthetic Al peptides (AIPs), which mimic naturally occurring AIPs. These groups inhibit receptors from binding substrate or decrease the concentration of receptors in the cell.[44] Furanones have also been found to act on AHL-dependant transcriptional activity, whereby the half life of the autoinducer-binding LuxR protein is significantly shortened.[46]
Recently, a well-studied quorum quenching bacterial strain (KM1S) was isolated and its AHL degradation kinetic was studied using rapid resolution liquid chromatography (RRLC).[47] RRLC efficiently separates components of a mixture to a high degree of sensitivity, based on their affinities for different liquid phases.[48] It was found that the genome of this strain encoded an inactivation enzyme with distinct motifs targeting the degradation of AHLs.[47]
Applications of quorum quenching that have been exploited by humans include the use of AHL-degrading bacteria in aquacultures to limit the spread of diseases in aquatic populations of fish, mollusks and crustaceans.[49]This technique has also been translated to agriculture, to restrict the spread of pathogenic bacteria that use quorum sensing in plants.[49][50] Anti-biofouling is another process that exploits quorum quenching bacteria to mediate the dissociation of unwanted biofilms aggregating on wet surfaces, such as medical devices, transportation infrastructure and water systems.[49][51]
Social insects[edit]
Social insect colonies are an excellent example of a decentralized system, because no individual is in charge of directing or making decisions for the colony. Several groups of social insects have been shown to use quorum sensing in a process that resembles collective decision-making.
Examples[edit]
Ants[edit]
Colonies of the ant Temnothorax albipennis nest in small crevices between rocks. When the rocks shift and the nest is broken up, these ants must quickly choose a new nest to move into. During the first phase of the decision-making process, a small portion of the workers leave the destroyed nest and search for new crevices. When one of these scout ants finds a potential nest, she assesses the quality of the crevice based on a variety of factors including the size of the interior, the number of openings (based on light level), and the presence or absence of dead ants.[52][53] The worker then returns to the destroyed nest, where she waits for a short period before recruiting other workers to follow her to the nest that she has found, using a process called tandem running. The waiting period is inversely related to the quality of the site; for instance, a worker that has found a poor site will wait longer than a worker that encountered a good site.[54] As the new recruits visit the potential nest site and make their own assessment of its quality, the number of ants visiting the crevice increases. During this stage, ants may be visiting many different potential nests. However, because of the differences in the waiting period, the number of ants in the best nest will tend to increase at the greatest rate. Eventually, the ants in this nest will sense that the rate at which they encounter other ants has exceeded a particular threshold, indicating that the quorum number has been reached.[55] Once the ants sense a quorum, they return to the destroyed nest and begin rapidly carrying the brood, queen, and fellow workers to the new nest. Scouts that are still tandem-running to other potential sites are also recruited to the new nest, and the entire colony moves. Thus, although no single worker may have visited and compared all of the available options, quorum sensing enables the colony as a whole to quickly make good decisions about where to move.
Honey bees[edit]
Honey bees (Apis mellifera) also use quorum sensing to make decisions about new nest sites. Large colonies reproduce through a process called swarming, in which the queen leaves the hive with a portion of the workers to form a new nest elsewhere. After leaving the nest, the workers form a swarm that hangs from a branch or overhanging structure. This swarm persists during the decision-making phase until a new nest site is chosen.
The quorum sensing process in honey bees is similar to the method used by Temnothorax ants in several ways. A small portion of the workers leave the swarm to search out new nest sites, and each worker assesses the quality of the cavity it finds. The worker then returns to the swarm and recruits other workers to her cavity using the honey bee waggle dance. However, instead of using a time delay, the number of dance repetitions the worker performs is dependent on the quality of the site. Workers that found poor nests stop dancing sooner, and can therefore be recruited to the better sites. Once the visitors to a new site sense that a quorum number (usually 10–20 bees) has been reached, they return to the swarm and begin using a new recruitment method called piping. This vibration signal causes the swarm to take off and fly to the new nest location. In an experimental test, this decision-making process enabled honey bee swarms to choose the best nest site in four out of five trials.[56][57]
Computing and robotics[edit]
Quorum sensing can be a useful tool for improving the function of self-organizing networks such as the SECOAS (Self-Organizing Collegiate Sensor) environmental monitoring system. In this system, individual nodes sense that there is a population of other nodes with similar data to report. The population then nominates just one node to report the data, resulting in power savings.[58] Ad-hoc wireless networks can also benefit from quorum sensing, by allowing the system to detect and respond to network conditions.[59]
Quorum sensing can also be used to coordinate the behavior of autonomous robot swarms. Using a process similar to that used by Temnothorax ants, robots can make rapid group decisions without the direction of a controller.[60]
See also[edit]
Cell signaling
Collective behavior
Interspecies quorum sensing
Microbial intelligence
Swarm intelligence
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Jump up ^ Britton, M.; Sacks, L. (2004). "The SECOAS Project—Development of a Self-Organising, Wireless Sensor Network for Environmental Monitoring" (PDF). SANPA. Archived from the original (PDF) on 2008-12-16.
Jump up ^ Peysakhov, M.; Regli, W. (2005). "Ant inspired server population management in a service based computing environment". Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005. Swarm Intelligence Symposium, Proceedings 2005 IEEE. pp. 357–64. doi:10.1109/SIS.2005.1501643. ISBN 0-7803-8916-6.
Jump up ^ Sahin, E.; Franks, N. (2002). "Measurement of Space: From Ants to Robots". Proceedings of WGW 2002: EPSRC/BBSRC International Workshop. CiteSeerX 10.1.1.161.6407  .
Further reading[edit]
Dedicated issue of Philosophical Transactions B on quorum sensing. Some articles are freely available.
External links[edit]
The Quorum Sensing Website
Cell-to-Cell Communication in Bacteria
The SECOAS project—Development of a Self-Organising, Wireless Sensor Network for Environmental Monitoring
Measurement of Space: From Ants to Robots
Instant insight into quorum sensing from the Royal Society of Chemistry
Bonnie Bassler: Discovering bacteria's amazing communication system
Bonnie Bassler's seminar: "Cell-Cell Communication in Bacteria"
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NFL win–loss records
From Wikipedia, the free encyclopedia
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The following is a list of win–loss records for each of the 32 active National Football League (NFL) teams.
Contents
[hide]
1 Regular season
2 Playoffs
3 Notes
4 References
Regular season[edit]
George Halas (right) of the Chicago Bears, who have recorded the most regular season wins.
The following is a listing of all 32 current National Football League (NFL) teams ranked by their regular season win–loss record percentage, accurate as of the end of the 2017 NFL regular season.[1] For teams that previously played in the All-America Football Conference (AAFC), their AAFC win-loss records are not included as the NFL does not officially count AAFC statistics despite the 1950 NFL–AAFC merger.[2][a] However, for teams that played in the American Football League (AFL), their AFL win-loss records are included and officially counted by the NFL. Ties are registered as a half win and a half loss when calculating the win-loss record.
Best win–loss record in division
Rank
Team
Won
Lost
Tied
Pct.
First NFL Season
Total Games
Division
1 Dallas Cowboys 502 374 6 .573 1960 882 NFC East
2 Green Bay Packers 737 562 37 .565 1921 1,336 NFC North
3 Chicago Bears 749 579 42 .562 1920 1,370 NFC North
4 Miami Dolphins 445 351 4 .559 1966 800 AFC East
5 New England Patriots[b] 489 386 9 .558 1960 884 AFC East
6 Minnesota Vikings 470 390 10 .546 1961 870 NFC North
7 Baltimore Ravens 190 161 1 .541 1996 352 AFC North
8 New York Giants 687 585 33 .539 1925 1,305 NFC East
9 Denver Broncos 470 404 10 .537 1960 884 AFC West
10 San Francisco 49ers 528 460 14 .534 1950 1,002 NFC West
11 Pittsburgh Steelers 614 538 20 .532 1933 1,172 AFC North
12 Oakland Raiders 462 411 11 .529 1960 884 AFC West
13 Indianapolis Colts[c] 506 453 7 .527 1953 966 AFC South
14 Kansas City Chiefs 457 415 12 .524 1960 884 AFC West
15 Seattle Seahawks 334 325 1 .507 1976 660 NFC West
16 Washington Redskins 595 581 28 .506 1932 1,202 NFC East
17 Carolina Panthers 183 184 1 .499 1995 368 NFC South
18 Los Angeles Chargers 435 438 11 .498 1960 884 AFC West
19 Los Angeles Rams 555 559 21 .498 1937 1,135 NFC West
20 Cleveland Browns 462 482 10 .490 1950 954 AFC North
21 Philadelphia Eagles 568 594 26 .489 1933 1,188 NFC East
22 Tennessee Titans 422 456 6 .481 1960 884 AFC South
23 Buffalo Bills 409 467 8 .467 1960 884 AFC East
24 Detroit Lions 553 648 32 .461 1930 1,233 NFC North
25 Cincinnati Bengals 351 417 4 .457 1968 772 AFC North
26 New York Jets 397 479 8 .454 1960 884 AFC East
27 Jacksonville Jaguars 165 203 0 .448 1995 368 AFC South
28 New Orleans Saints 349 432 5 .447 1967 786 NFC South
29 Atlanta Falcons 351 443 6 .443 1966 790 NFC South
30 Houston Texans 110 146 0 .430 2002 256 AFC South
31 Arizona Cardinals 550 740 40 .429 1920 1,330 NFC West
32 Tampa Bay Buccaneers 255 404 1 .387 1976 660 NFC South
Playoffs[edit]
Members of the Baltimore Ravens franchise, the team with the highest playoff win–loss percentage, during the Lombardi Trophy presentation following their Super Bowl XLVII victory
Marvin Lewis, head coach of the Cincinnati Bengals, who have registered the lowest playoff win-loss percentage of all time
The following is a listing of all 32 current National Football League (NFL) teams ranked by their playoff win-loss record percentage, accurate as of the end of 2017–18 NFL Wild Card round.
Best win–loss record in division
Team active in playoffs
Rank
Team
Games
Won
Lost
Pct.
Last playoff
appearance
Division
1 Baltimore Ravens 23 15 8 .652 2014 AFC North
2 New England Patriots 53 34 19 .642 2017 AFC East
3 Green Bay Packers 56 34 22 .607 2016 NFC North
4 San Francisco 49ers 50 30 20 .600 2013 NFC West
5 Pittsburgh Steelers 61 36 25 .590 2017 AFC North
6 Oakland Raiders 44 25 19 .568 2016 AFC West
7 Dallas Cowboys 61 34 27 .557 2016 NFC East
8 (tie) Denver Broncos 42 23 19 .548 2015 AFC West
8 (tie) Washington Redskins 42 23 19 .548 2015 NFC East
10 Carolina Panthers 17 9 8 .529 2017 NFC South
11 Seattle Seahawks 31 16 15 .516 2016 NFC West
12 (tie) Philadelphia Eagles 42 21 21 .500 2017 NFC East
12 (tie) Jacksonville Jaguars 14 7 7 .500 2017 AFC South
14 New York Giants 49 24 25 .490 2016 NFC East
15 Indianapolis Colts 45 22 23 .489 2014 AFC South
16 Miami Dolphins 41 20 21 .488 2016 AFC East
17 Chicago Bears 35 17 18 .486 2010 NFC North
18 New York Jets 25 12 13 .480 2010 AFC East
19 Buffalo Bills 30 14 16 .467 2017 AFC East
20 New Orleans Saints 18 8 10 .444 2017 NFC South
21 Arizona Cardinals 16 7 9 .438 2015 NFC West
22 Los Angeles Rams 44 19 25 .432 2017 NFC West
23 (tie) Tennessee Titans 35 15 20 .429 2017 AFC South
23 (tie) Houston Texans 7 3 4 .429 2016 AFC South
25 Atlanta Falcons 24 10 14 .417 2017 NFC South
26 Minnesota Vikings 49 20 29 .408 2017 NFC North
27 Tampa Bay Buccaneers 15 6 9 .400 2007 NFC South
28 Los Angeles Chargers 28 11 17 .393 2013 AFC West
29 Cleveland Browns 31 11 20 .355 2002 AFC North
30 Detroit Lions 20 7 13 .350 2016 NFC North
31 Kansas City Chiefs 27 9 18 .333 2017 AFC West
32 Cincinnati Bengals 19 5 14 .263 2015 AFC North
Notes[edit]
Jump up ^ For example, the Browns' regular season win–loss record does not include a 47–4–3 record compiled in the All-America Football Conference from 1946 to 1949, nor does their playoff record include the 5–0 record compiled during the same period. Likewise, the 49ers' AAFC regular season win–loss record of 38–14–2, nor their 1-1 AAFC playoff record are officially counted
Jump up ^ The Patriots played as the "Boston Patriots" from 1960–1970, before adopting the "New England Patriots" name, which they have played under since the 1971 season.[3] The team was also briefly known as the "Bay State Patriots" prior to the 1971 season.[4]
Jump up ^ The Colts played under the "Baltimore Colts" name from 1953–1983, before relocating to Indianapolis and adpoting their current "Indianapolis Colts" name, which they have played under since the 1984 season.[5]
References[edit]
Jump up ^ "Franchise Encyclopedias". Pro Football Reference. Sports-Reference. Retrieved January 14, 2016.
Jump up ^ Brown, Daniel; Emmons, Mark (November 8, 2011). "49ers great Joe Perry and the stats that don't count". San Jose Mercury News. Retrieved January 14, 2016.
Jump up ^ "New England Patriots — Team History". Pro Football Hall of Fame. Retrieved October 17, 2017.
Jump up ^ Dewdney, Mike (February 21, 2012). "The Rise and Fall of the Bay State Patriots". Chris Creamer's Sports Logos. Retrieved October 17, 2017.
Jump up ^ Hensley, Jamison (March 28, 2014). "30 years on, Baltimore better without Colts". ESPN. Retrieved October 17, 2017.
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National Football League (2017)
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East North South West
Buffalo Bills
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New England Patriots
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Cincinnati Bengals
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Houston Texans
Indianapolis Colts
Jacksonville Jaguars
Tennessee Titans
Denver Broncos
Kansas City Chiefs
Los Angeles Chargers
Oakland Raiders
NFC
East North South West
Dallas Cowboys
New York Giants
Philadelphia Eagles
Washington Redskins
Chicago Bears
Detroit Lions
Green Bay Packers
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