Information

16.4: Overview - Biology

16.4: Overview - Biology


We are searching data for your request:

Forums and discussions:
Manuals and reference books:
Data from registers:
Wait the end of the search in all databases.
Upon completion, a link will appear to access the found materials.

Official course description:This course is designed to explore the biological aging process as part of the normal developmental sequence and process of change from conception to death. This aging process will be viewed as the developmental continuum that occurs in all human beings. Typical biological aging changes in all body systems, as well as some disease processes, will be discussed.
Credits: 3
Course prerequisites: None

This course is fully online. Each scheduled module may include readings, discussion, quizzes, and written assignments.

Module 1: Introduction to Human Again, Theories of Aging, and Cellular Aging
Module 2: The Integumentary System, Skeletal System, and Muscular System
Module 3: The Nervous System & Special Senses
Module 4: The Circulatory, Immune, and Respiratory System
Module 5: The Digestive and Urinary System
Module 6: The Reproductive and Endocrine System
Module 7: Term Research Project


16.4: Overview - Biology

Prokaryotes exhibit much more nutritional diversity than eukayotes.

Two sources of energy are used: Photographs capture energy from the sunlight and Chemotrophs which harness energy stored in chemicals.

Two sources of carbon are used by prokaryotes:
Autotrophs obtain carbon atoms from carbon dioxide.
Heterotrophs obtain their carbon atoms from the organic compounds present in other organisms.

The terms that describe how prokaryotes obtain energy and carbon are combined to describe their modes of nutrition:
-Photoautotrophs obtain energy from sunlight and use carbon dioxide for carbon.
-Photoheterotrophs obtain energy from sunlight but get their carbon atoms from organic molecules.
-Chemoautotrophs harvest energy from inorganic chemicals and use carbon dioxide for carbon.
-Chemoheterotrophs acquire energy and carbon from organic molecules.

A quick and simple view of the above information can be seen below in purple.

Photoauthotroph
Energy source: Sunlight
Carbon source: CO2

Chemoautotroph
Energy source: Inorganic materials
Carbon source: CO2

Photoheterotroph
Energy source: Sunlight
Carbon source: Organic compounds

Chemoheterotrop
Energy source: Organic compounds
Carbon source: Organic compounds


16.4: Overview - Biology

Pantry staples from the genetic swap meet - May, 2021
To many people, genetically engineered food feels unnatural and repellent: Fish genes in strawberries? No thanks. Opponents often call them "Frankenfoods," suggesting that only a mad scientist could combine genes from different species in this way. But in recent decades, biologists have found that nature itself often plays fast and loose with DNA. Now, new research shows how important this inter-species genetic swap meet has been in grasses, a group that includes food staples like rice, corn, wheat, and sugar cane.

A Pleistocene Puzzle: Extinction in South America
In this comic, you'll follow the investigation of scientists Maria and Miguel as they solve a paleontological mystery. About 11,000 years ago, more than 80% of the large animal species in South America went extinct. Why did it happen? Maria and Miguel study an area in Chile called Ultima Esperanza. They discover many different lines of evidence that point to a warming climate and the arrival of humans as key causes of the extinctions.


Contents

In May 1998, Volkswagen AG acquired the rights to use the Bugatti logo and the trade name Bugatti Automobiles S.A.S. To succeed the EB 110 model produced under the previous ownership, the automaker quickly released a series of concept cars whose technological advancements would culminate in the form of the Veyron 16.4.

Between October 1998 and September 1999, Bugatti introduced a series of Giugiaro-designed concept vehicles, each with permanent four-wheel drive and powered by the Volkswagen-designed W18 engine. The first car, the EB 118, was a 2-door luxury coupé presented at the 1998 Paris Motor Show. The next car, the EB218, was a 4-door saloon presented at the 1999 Geneva Motor Show. The third and final car, the 18/3 Chiron, was a mid-engine sports car presented at the 1999 International Motor Show in Frankfurt. [18]

In October 1999, Bugatti unveiled a fourth concept car at the Tokyo Motor Show. The EB 18/4 Veyron was a mid-engine sports car styled in-house under the direction of Hartmut Warkuß. [19] In 2000, a modified version, the EB 16/4 Veyron, was displayed at motor shows in Detroit, Geneva, and Paris. Rather than the three-bank W18 engine of the four previous concept cars, the EB 16/4 featured the four-bank W16 engine architecture installed in every production example of the Veyron. [20]

The decision to start production of the car was made by the Volkswagen Group in 2001. The first roadworthy prototype was completed in August 2003. It is identical to the later series variant, except for a few details. In the transition from development to series production, considerable technical problems had to be addressed, repeatedly delaying production until September 2005. [21]

The Veyron EB 16.4 is named in honor of Pierre Veyron, a Bugatti development engineer, test driver and company race driver who, with co-driver Jean-Pierre Wimille, won the 1939 24 Hours of Le Mans while driving a Bugatti. [22] The "EB" refers to Bugatti founder Ettore Bugatti and the "16.4" refers to the engine's 16 cylinders and quad-turbochargers. [23]

Bugatti Veyron (2005–2011) Edit

Specifications and performance Edit

The Veyron features an 8.0-litre, quad-turbocharged, W16 cylinder engine, equivalent to two narrow-angle V8 engines bolted together. Each cylinder has four valves for a total of 64, but the configuration of each bank allows two overhead camshafts to drive two banks of cylinders so only four camshafts are needed. The engine is fed by four turbochargers and displaces 7,993 cc (487.8 cu in), with a square 86 by 86 mm (3.39 by 3.39 in) bore and stroke.

The transmission is a dual-clutch direct-shift computer-controlled automatic transmission having seven gear ratios, with magnesium paddles behind the steering wheel and a shift time of less than 150 milliseconds, built by Ricardo of England rather than Borg-Warner, who designed the six speed DSG used in the mainstream Volkswagen Group marques. The Veyron can be driven in either semi-automatic or fully-automatic mode. A replacement transmission for the Veyron costs just over US$120,000 . [24] It also has permanent all-wheel drive using the Haldex Traction system. It uses special Michelin PAX run-flat tyres, designed specifically to accommodate the Veyron's top speed, and cost US$25,000 per set. [24] The tyres can be mounted on the wheels only in France, a service which costs US$70,000 . [24] Kerb weight is 1,888 kg (4,162 lb). [25] This gives the car a power-to-weight ratio, according to Volkswagen Group's figures, of 530 PS (390 kW 523 hp) per ton. The car's wheelbase is 2,710 mm (106.7 in). Overall length is 4,462 mm (175.7 in) which gives 1,752.6 mm (69.0 in) of overhang. The width is 1,998 mm (78.7 in) and height 1,204 mm (47.4 in). The Bugatti Veyron has a total of ten radiators: [26]

  • 3 heat exchangers for the air-to-liquid intercoolers.
  • 3 engine radiators.
  • 1 for the air conditioning system.
  • 1 transmission oil radiator.
  • 1 differential oil radiator.
  • 1 engine oil radiator

It has a drag coefficient of Cd=0.41 (normal condition) and Cd=0.36 (after lowering to the ground), [27] and a frontal area of 2.07 m 2 (22.3 sq ft). [28] This gives it a drag area, the product of drag coefficient and frontal area, of CdA=0.74 m 2 (8.0 sq ft).

Engine power output Edit

According to Volkswagen Group and certified by TÜV Süddeutschland, the W16 engine utilised by the Veyron has a power output of 736 kW (987 hp 1,001 PS), and generates 1,250 N⋅m (922 lbf⋅ft) of torque. [4] [29] [30]

Top speed Edit

German inspection officials recorded an average top speed of the original version at 408.47 km/h (253.81 mph) [11] during test sessions on Volkswagen Group's private Ehra-Lessien test track on 19 April 2005.

This top speed was almost matched by James May on Top Gear in November 2006, at the Ehra-Lessien test track, at 407.5 km/h (253.2 mph). [11] May noted that at top speed the engine consumes 45,000 L (9,900 imp gal) of air per minute (as much as a human breathes in four days). Back in the Top Gear studio, co-presenter Jeremy Clarkson commented that most sports cars felt like they were shaking apart at their top speed, and asked May if that was the case with the Veyron at 407 km/h (253 mph). May responded that the Veyron was very controlled, and only wobbled slightly when the air brake deployed. [31]

The car's normal top speed is listed at 343 km/h (213 mph). When the car reaches 220 km/h (137 mph), hydraulics lower the car until it has a ground clearance of about 9 cm (3.5 in). At the same time, the wing and spoiler deploy. In this handling mode, the wing provides 3,425 newtons (770 lbf) of downforce, holding the car to the road. [26]

Top speed mode must be entered while the vehicle is at rest. Its driver must toggle a special top speed key to the left of their seat, which triggers a checklist to establish whether the car and its driver are ready to attempt to reach 407 km/h (253 mph). If so, the rear spoiler retracts, the front air diffusers shut, and normal 12.5 cm (4.9 in) ground clearance drops to 6.5 cm (2.6 in).

Braking Edit

The Veyron's brakes use cross drilled, radially vented carbon fibre reinforced silicon carbide (C/SiC) composite discs, manufactured by SGL Carbon, which have less brake fade and weigh less than standard cast iron discs. [32] The lightweight aluminium alloy monobloc brake calipers are made by AP Racing the front have eight [26] titanium pistons and the rear calipers have six pistons. Bugatti claims maximum deceleration of 1.3 g on road tyres. As an added safety feature, in the event of brake failure, an anti-lock braking system (ABS) has also been installed on the handbrake.

Prototypes have been subjected to repeated 1.0 g braking from 312 km/h (194 mph) to 80 km/h (50 mph) without fade. With the car's acceleration from 80 km/h (50 mph) to 312 km/h (194 mph), that test can be performed every 22 seconds. At speeds above 200 km/h (124 mph), the rear wing also acts as an airbrake, snapping to a 55° angle in 0.4 seconds once brakes are applied, providing an additional 0.68 g (6.66 m/s 2 ) of deceleration (equivalent to the stopping power of an ordinary hatchback). [26] Bugatti claims the Veyron will brake from 400 km/h (249 mph) to a standstill in less than 10 seconds, though distance covered in this time will be half a kilometre (third of a mile). [26]

Special editions Edit

Name Picture Release date Release price Notes
Bugatti 16.4 Veyron Pur Sang [33] September 2007 5 units were made.
Bugatti Veyron Fbg par Hermès [34] March 2008 €1.55 million, excluding taxes and transport [35] This model was limited to four units. A Veyron 16.4 Grand Sport was later produced in the same configuration.
Bugatti 16.4 Veyron Sang Noir [36] May 2008 12 units were made.
Bugatti Veyron Bleu Centenaire [37] March 2009 One of a kind.
Bugatti Veyron "Jean-Pierre Wimille" [38] September 2009
Bugatti Veyron "Achille Varzi" September 2009
Bugatti Veyron "Malcolm Campbell" September 2009
Bugatti Veyron "Hermann zu Leiningen" September 2009

Bugatti Veyron 16.4 Grand Sport (2009–2015) Edit

The targa top version of the Bugatti Veyron EB 16.4, dubbed the Bugatti Veyron 16.4 Grand Sport, was unveiled at the 2008 Pebble Beach Concours d'Elegance. [39] [40] It has extensive reinforcements to compensate for the lack of a standard roof [41] and small changes to the windshield and running lights. Two removable tops are included, the second a temporary arrangement fashioned after an umbrella. The top speed with the hardtop in place is the same as the standard coupé version, but with the roof removed is limited to 369 km/h (229 mph)—and to 130 km/h (81 mph) with the temporary soft roof. The Grand Sport edition was limited to 150 units, with the first 50 going exclusively to registered Bugatti customers. Production began in the second quarter of 2009.

Special editions Edit

Name Picture Release date Release price Notes
Bugatti Veyron 16.4 Grand Sport Sang Bleu [42] August 2009 [43] One of a kind.
Bugatti Veyron 16.4 Grand Sport L'Or Blanc [44] June 2011 €1.65 million, excluding taxes and transport Collaboration between Bugatti and the Royal Porcelain Factory in Berlin.
Bugatti Veyron 16.4 Grand Sport "Dubai Motor Show 2011" Special Edition [45] November 2011 €1.58 million, excluding taxes and transport Introduced with a horizontal colour split with a bright yellow body framed in visible black carbon (including black-tinted wheels), seats in yellow-coloured leather upholstery with black stitching, middle console in black carbon, dashboard, steering wheel and gearshift made of black leather with yellow stitching. [46] The car was then shown again at the 2012 Qatar Motor Show.
Bugatti Veyron 16.4 Grand Sport "Dubai Motor Show 2011" Special Edition November 2011 €1.74 million, excluding taxes and transport Presented in a two-tone horizontal colour split consisting of visible blue carbon, framed in polished, anodised aluminium.
Bugatti Veyron 16.4 Grand Sport "Dubai Motor Show 2011" Special Edition November 2011 €1.74 million, excluding taxes and transport Came in the newly developed green carbon fibre tone with polished aluminium.
Bugatti Veyron 16.4 Grand Sport Bernar Venet [47] December 2012 [48] One of a kind.

Bugatti Veyron 16.4 Super Sport, World Record Edition (2010–2011) Edit

The Bugatti Veyron 16.4 Super Sport is a faster, more powerful version of the Bugatti Veyron 16.4. Production was limited to 30 units. The Super Sport has increased engine power output of 1,200 PS (883 kW 1,184 hp) at 6,400 rpm and a maximum torque of 1,500 N⋅m (1,106 lb⋅ft) at 3,000–5,000 rpm and a revised aerodynamic package. [49] The Super Sport has been driven as fast as 431.072 km/h (267.856 mph), making it the fastest production road car in the world at the time of its introduction [5] [50] [51] although it is electronically limited to 415 km/h (258 mph) to protect the tyres from disintegrating. [49]

The Bugatti Veyron 16.4 Super Sport World Record Edition is a version of the Bugatti Veyron 16.4 SuperSport. It is limited to five units. It has an orange body detailing, orange wheels, and a special black exposed carbon body. The electronic limiter is also removed with this version. [52]

The model was unveiled in 2010 at The Quail, followed by the 2010 Monterey Historic Races at Laguna Seca, and the 2010 Pebble Beach Concours d'Elegance. [53]

Top Speed World Record Edit

On 4 July 2010 James May, a television presenter on BBC Two's television show Top Gear, drove the Veyron Super Sport on Volkswagen's Ehra-Lessien (near Wolfsburg, Germany) high-speed test track at 417.61 km/h (259.49 mph). Later that day, Bugatti's official test driver Pierre Henri Raphanel drove the Super Sport version of the Veyron at the same track to establish the car's top speed. With representatives of the Guinness Book of Records and German Technical Inspection Agency (TÜV) on hand, Raphanel made passes around the big oval in both directions achieving an average maximum speed of 431.072 km/h (267.856 mph), thus taking back the title from the SSC Ultimate Aero TT as the fastest production vehicle of all time. [12] The 431.072 km/h mark was reached by averaging the Super Sport's two test runs, the first reaching 427.933 km/h (265.905 mph) and the second 434.211 km/h (269.806 mph). [54] [55]

When the record was certified it was already well known to the public that the customer car would be electronically limited to 415 km/h (258 mph). Yet, after a query by the Sunday Times Guinness' PR director Jaime Strang was quoted on 5 April 2013: "As the car's speed limiter was deactivated, this modification was against the official guidelines. Consequently, the vehicle's record set at 431.072 km/h is no longer valid." On 10 April 2013, it was written on its website: "Guinness World Records would like to confirm that Bugatti's record has not been disqualified the record category is currently under review."

On 15 April 2013 Bugatti's speed record was confirmed: "Following a thorough review conducted with a number of external experts, Guinness World Records is pleased to announce the confirmation of Bugatti's record of Fastest production car achieved by the Veyron 16.4 SuperSport. The focus of the review was with respect to what may constitute a modification to a car's standard specification. Having evaluated all the necessary information, Guinness World Records is now satisfied that a change to the speed limiter does not alter the fundamental design of the car or its engine." [56] [57] [58]

Bugatti Veyron 16.4 Grand Sport Vitesse (2012–2015) Edit

The Bugatti Veyron 16.4 Grand Sport Vitesse is a targa top version of the Veyron Super Sport. The engine in the Vitesse variant has a maximum power output of 1,200 PS (883 kW 1,184 bhp) at 6,400 rpm and a maximum torque of 1,500 N⋅m (1,100 lb⋅ft) at 3,000–5,000 rpm. These figures allow the car to accelerate from a stand still to 100 km/h (62 mph) in 2.6 seconds. On normal roads, the Vitesse is electronically limited to 375 km/h (233 mph).

The Vitesse was first unveiled at the 2012 Geneva Motor Show [59] [60] and later at the 2012 Beijing Auto Show [61] and the 2012 São Paulo Motor Show. [62]

Special editions Edit

A number of special editions of the Vitesse were made:

  • The World Record Car (WRC) Edition was limited to 8 units, debuted in 2013, and went on sale for €1.99 million. [63][64][65]

In 2013, Bugatti produced a series of Vitesse dedicated to racing legends, including Jean-Pierre Wimille [71] [72] Jean Bugatti, [73] [74] Meo Costantini, [75] and Ettore Bugatti. [76]

All six models in the Legend series are limited to three vehicles: [77]

Name Picture Release date Release price Notes
Bugatti Legend "Jean-Pierre Wimille" [78] 24 July 2013
Bugatti Legend "Jean Bugatti" [79] 9 September 2013 €2.28 million, excluding taxes and transport
Bugatti Legend "Meo Costantini" [80] 5 November 2013 €2.09 million, excluding taxes and transport This model is reminiscent of the Bugatti Type 35. One of the three model made, the only US-spec car, was sold in August 2020 at Bonhams Quail auction for US$ 1,750,000 inc. premium. [81]
Bugatti Legend "Rembrandt Bugatti" [82] [83] 3 March 2014 €2.18 million, excluding taxes and transport Rembrandt Bugatti was the brother of company founder Ettore and one of the most important sculptors of the 20th century.
"Black Bess" Legend Vitesse [84] [85] 10 April 2014 €2.15 million, excluding taxes and transport This model is reminiscent of the famed Bugatti Type 18 "Black Bess".
Bugatti Legend "Ettore Bugatti" [86] 7 August 2014 €2.35 million, excluding taxes and transport This model harks back to the Bugatti Type 41 Royale.

Records Edit

A Bugatti Veyron 16.4 Grand Sport Vitesse driven by the Chinese racing driver Anthony Liu at Volkswagen Group's proving grounds in Ehra-Lessien became the fastest open-top production sports car, with a top speed of 408.84 km/h (254.04 mph). [64]

After the world record attempt, Dr. Wolfgang Schreiber, President of Bugatti Automobiles S.A.S, said "When we introduced the Vitesse, we established the top speed for open-top driving to be 375 km/h. Still, we could not let go of the idea of reaching the 400 km/h mark with this car as well. The fact that we have succeeded in reaching 408.84 km/h is a thrill for me, and it reaffirms once again that Bugatti is the leader when it comes to technology in the international automotive industry." The driver, Anthony Liu, claimed "Even at such high speeds it remained incredibly comfortable and stable. With an open-top, you can really experience the sound of the engine and yet even at higher speeds I did not get compromised by the wind at all." [63]

Basic specifications [4] [5]
Layout and body style Mid-engine, four-wheel drive, two-door coupé/targa top Base price Standard (Coupé), Grand Sport (Roadster):
€1,225,000 ( £1,065,000 US$1,700,000 )
Super Sport (Coupé), Grand Sport Vitesse (Roadster):
€1,912,500 ( £1,665,000 US$2,700,000 )
Internal combustion engine 8.0 litre W16, 64v 2xDOHC quad-turbocharged petrol engine Engine displacement
and max. power
7,993 cc (487.8 cu in)
Standard (Coupé), Grand Sport (Roadster):
736 kW (987 hp 1,001 PS) at 6,000 rpm
Super Sport (Coupé), Grand Sport Vitesse (Roadster):
883 kilowatts (1,201 PS 1,184 bhp) at 6,400 rpm
Performance
Standard, Grand Sport Super Sport, Grand Sport Vitesse
Top Speed 408.47 km/h (253.81 mph) [87] 431.072 km/h (267.856 mph) 415 km/h (258 mph) limited [55]
0–100 km/h (62 mph) 2.46 seconds [88] [89]
0–200 km/h (124 mph) 7.3 seconds [90] [91] 6.7 seconds [92] [93]
0–300 km/h (186 mph) 16.7 seconds [90] [91] 14.6 seconds [92] [93]
0–400 km/h (249 mph) 55.6 seconds [91] 40 seconds [ citation needed ] (estimated) [ by whom? ]
Standing quarter-mile (402 m) 10.1 seconds [94] 9.7 seconds [92]
Standing mile (1609 m) 25.9 seconds at 204.4 mph [95] 23.6 seconds [92]
Braking from 100 km/h (62 mph) 31.4 m [90] [92]
0–300–0 km/h 27.8 seconds [96] 22.5 seconds [92]
0–200–0 mph 25.6 seconds [92]
Lateral acceleration ? 1.4 g [92]
Fuel economy [97]
EPA city driving 8 miles per U.S. gallon (29 L/100 km 9.6 mpg‑imp) EPA highway driving 14 miles per U.S. gallon (17 L/100 km 17 mpg‑imp)
Top speed fuel economy 3 miles per U.S. gallon (78 L/100 km 3.6 mpg‑imp), or 1.4 U.S. gal (5.3 L 1.2 imp gal) per minute

As of 6 August 2014 [update] , 405 cars have been produced and delivered to customers worldwide, with orders that have already been placed for another 30. Bugatti was reported to produce 300 coupés and 150 roadsters up to the end of 2015. [98] Production amounted to 450 units in a span of over 10 years. The final production vehicle, a Grand Sport Vitesse titled "La Finale" (The Last One), was displayed at the Geneva Motor Show from 5–15 March 2015. [99]

Name Units made
Veyron 16.4 252
Grand Sport 58
Super Sport 48
Grand Sport Vitesse 92
Total 450

In 2008, Bugatti then-CEO Dr Franz-Josef Paefgen confirmed that the Veyron would be replaced by another high-end model by 2012. [100] In 2011, the new CEO Wolfgang Dürheimer revealed that the company was planning to produce two models in the future — one a sports car-successor to the Veyron, the other a limousine known as the Bugatti 16C Galibier, which was later cancelled since Bugatti was later then working on a successor to the Veyron, which became the Bugatti Chiron. [101]

The successor to the Veyron was unveiled in concept form as the Bugatti Vision Gran Turismo at the September 2015 Frankfurt Motor Show.

A toned-down version of the radically styled Vision Gran Turismo concept car, now called the Chiron, debuted at the March 2016 Geneva Motor Show. Production started in 2017 and will be limited to 500 units.

Year Units sold
2005 5 [102]
2006 44 [102]
2007 81 [103]
2008 71 [104]
2009 50 [104]
2010 40 [105]
2011 38 [106] 1
2012 31 [107]
2013 47 [108]
Total 407 ISI

Top Gear Edit

All three former presenters of the popular BBC motoring show Top Gear have given the Veyron considerable praise. While initially skeptical that the Veyron would ever be produced, Jeremy Clarkson later declared the Veyron "the greatest car ever made and the greatest car we will ever see in our lifetime", comparing it to Concorde and S.S. Great Britain. He noted that the production cost of a Veyron was GB£5 million , but was sold to customers for just GB£1 million . Volkswagen designed the car merely as a technical exercise. James May described the Veyron as "our Concorde moment". Clarkson test drove the Veyron from Alba in northern Italy to London in a race against May and Richard Hammond who made the journey in a Cessna 182 aeroplane.

A few episodes later, May drove the Veyron at the VW test track and took it to its top speed of 407.16 km/h (253.00 mph). In series 10, Hammond raced the Veyron against the Eurofighter Typhoon and lost. He also raced the car in Series 13 against a McLaren F1 driven by The Stig in a one-mile (1.6 km) drag race in Abu Dhabi. The commentary focused on Bugatti's "amazing technical achievement" versus the "non-gizmo" racing purity of the F1. While the F1 was quicker off the line and remained ahead until both cars were travelling at approximately 200 km/h, the Bugatti overtook its competitor from 200 to 300 km/h and emerged the victor. Hammond has stated that he did not use the Veyron's launch control in order to make the race more interesting.

The Veyron also won the award for "Car of the Decade" in Top Gear 's end of 2010 award show. Clarkson commented, "It was a car that just rewrote the rule book really, an amazing piece of engineering, a genuine Concorde moment". When the standard version was tested in 2008, it did not reach the top of the lap time leader board, with a time of 1:18.3, which was speculated as being due to the car's considerable weight disadvantage against the other cars towards the top. In 2010 the SuperSport version achieved the fastest ever time of 1:16.8 (dethroned the Gumpert Apollo S, replaced by the Ariel Atom V8 in 2011), [109] as well as being taken to a verified average top speed of 431 km/h (268 mph) by Raphanel on the programme, [110] thenceforth retaking its position as the fastest production car in the world. [111] [112] [113]

Martin Roach Edit

In 2011, Martin Roach's book Bugatti Veyron: A Quest for Perfection – The Story of the Greatest Car in the World [114] took the stance that the car had now become so famous that it is effectively a bona fide celebrity. The book follows its author as he attempts to track down and drive the car, along the way interviewing chief designers, test drivers, and the president of Bugatti.

Gordon Murray Edit

During its development period McLaren F1 designer Gordon Murray said in UK auto magazine Evo: "The most pointless exercise on the planet has got to be this four-wheel-drive, thousand-horsepower Bugatti." But after driving it he called it "a huge achievement". [115]

Murray was impressed with the Veyron's engine and transmission after he test drove one for Road & Track magazine. He also praised its styling: "The styling is a wonderful mélange of classic curves and mechanical edges and elements — this should ensure that the car will still look good years from now, and therefore have a chance of becoming a future classic." [116]


Southern Research Station

Pyemotes parviscolyti Cross & Moser is phoretic only on Pityophthorus bisulcatus Eichhoff it attacks all stages of this insect except the adult. Females, which contain little or no venom, prey on other scolytids if galleries overlap. Males copulate with females of Pyemotes ventricosus Newport and vice versa, but only males of the mother species result. Copulation with Pyemotes scolyti Oudeman's was not successful.

  • Citation: Moser, John c. Cross, E.A. 1971. Biology of Pyemotes parviscolyti (acarina: pyemotidae). Entomophaga, Vol.16(4): 367-379
  • Posted Date: April 20, 2006
  • Modified Date: August 22, 2006

Print Publications Are No Longer Available

In an ongoing effort to be fiscally responsible, the Southern Research Station (SRS) will no longer produce and distribute hard copies of our publications. Many SRS publications are available at cost via the Government Printing Office (GPO). Electronic versions of publications may be downloaded, printed, and distributed.


Contents

Categories Edit

There are three categories (strategies) of bet-hedging: "conservative" bet-hedging, "diversified" bet-hedging, and "adaptive coin flipping."

Conservative bet hedging Edit

In conservative bet hedging, individuals lower their expected fitness in exchange for a lower variance in fitness. The idea of this strategy is for an organism to "always play it safe" by using the same successful low-risk strategy regardless of environmental conditions. [6] An example of this would be an organism producing clutches with a constant egg size that may not be optimal for any environmental condition, but result in the lowest overall variance. [6]

Diversified bet hedging Edit

In contrast to conservative bet hedging, diversified bet hedging occurs when individuals lower their expected fitness in a given year while also increasing the variance of survival between offspring. This strategy uses the idea of not "putting all of your eggs in a basket." [6] Individuals implementing this strategy actually invest in several different strategies at once, resulting in low variation in long-term success. This could be demonstrated by a clutch of eggs of different sizes, each optimal for one potential environment of the offspring. While this means that offspring specialized for another environment are less likely to survive to adulthood, it also protects against the possibility of no offspring surviving to the next year. [6]

Adaptive coin flipping Edit

An individual using this type of bet hedging chooses what strategy to use based on a prediction of what the environment will be like. Organisms using this form of bet hedging make these predictions and select strategies annually. For example, an organism may produce clutches of different egg sizes from year to year, increasing variation in offspring success between clutches. [6] Unlike conservative and diversified bet hedging strategies, adaptive coin flipping isn't concerned with minimizing the variation in fitness between years.

To determine if a bet hedging allele is favored, the long-term fitness of each allele must be compared. Particularly in highly variable environments where bet hedging is likely to evolve, long-term fitness is best measured using the geometric mean, [7] which is multiplicative instead of additive like the arithmetic mean. The geometric mean is highly sensitive to small values. Even rare occurrences of zero fitness for a genotype result in it having an expected geometric mean of zero. This makes it appropriate for circumstances where a single genotype may have variable fitness depending on environmental circumstances.

Bet hedging is understood to be a mode of response to environmental change. [8] Adaptations that allow organisms to survive in fluctuating environmental conditions provide an evolutionary advantage. While a bet hedging trait may not be optimal for any one environment, this is outweighed by the benefits of higher fitness across a variety of environments. Therefore, bet hedging alleles tend to be favored in more variable environments. In order for a bet hedging allele to spread, it must persist in the typical environment through genetic drift long enough for alternative environments, in which the bet hedger has an advantage over genotypes adapted to the previous environment, to occur. Over many subsequent environmental alternations, selection may sweep the allele to fixation. [9]

A common example used when describing bet hedging is comparing the arithmetic and geometric fitness between specialist and bet hedging genotypes. [10] [11] The table below shows the relative fitness of four phenotypes in 'good' and 'bad' years and their respective means if 'good' years occur 75% of the time and 'bad' years 25% of the time.

The good year specialist has the highest fitness during a good year but does very poorly during a bad year, while the reverse is true for a bad year specialist. The conservative bet hedger does equally well in all years and the diversified bet hedger in this example uses the two specialist strategies each 50% of the time they perform better than the conservative bet hedger in good years, but worse during a bad year.

In this example, fitness is approximately equal within the specialist and bet hedger strategies, with the bet hedgers having a significantly higher fitness than the specialists. While the good year specialist' has the highest arithmetic mean, the bet hedging strategies are still preferred due to their higher geometric mean.

It is also important to realize that the fitness of any strategy is dependent on a large number of factors, such as the ratio of good to bad years and its relative fitness between good and bad years. Small changes in the strategies or environment having a large impact on which is optimal. In the above example, the diversified bet hedger outweighs the conservative bet hedger if it uses the good year specialist strategy more often. In contrast, if the relative fitness of the good year specialist was 0.35 in a bad year, it becomes the optimal strategy.

Prokarya Edit

Experiments in bet hedging using prokaryotic model organisms provide some of the most simplified views of the evolution of bet hedging. As bet hedging involves a stochastic switching between phenotypes across generations, [12] prokaryotes are able to display this phenomenon quite nicely due to their ability to reproduce quickly enough to track evolution in a single population over a short period of time. This rapid rate of reproduction has allowed for the study of bet hedging in labs through experimental evolution models. These models have been used to deduce the evolutionary origins of bet hedging.

Within prokarya, there are a multitude of bet hedging examples. In one example, the bacterium Sinorhizobium meliloti stores carbon and energy in a compound known as poly-3-hydroxybutyrate (PHB) in order to withstand carbon-deficient environments. When starved, S. meliloti populations begin to display bet hedging by forming two non-identical daughter cells during binary fission. The daughter cells display either low PHB levels or high PHB levels, which are better suited to short and long-term starvation, respectively. It has been reported that the low-PHB must compete effectively for resources in order to survive, whereas the high-PHB cells can survive for over a year without food. In this example, the PHB phenotype is being ‘bet-hedged’, as the survivability of the offspring largely depends on their environment, where only one phenotype is likely to survive under specific conditions. [13]

Another example of bet hedging arises in Mycobacterium tuberculosis. In a given population of this bacteria, persister cells exist with the ability to arrest their growth, which leaves them unaffected by dramatic changes to the environment. Once the persister cells grow to form another population of its species, which may or may not be antibiotic resistant, they will produce both cells with normal cell growth and another population of persisters to continue this cycle as the case may be. The ability to switch between the persister and normal phenotype is a form of bet-hedging. [14]

Prokaryotic persistence as a method of bet hedging is thus of importance to the field of medicine due to bacterial persistence. Because bet hedging is designed to produce genetically diverse offspring randomly in order to survive catastrophe, it is difficult to develop treatments for bacterial infections, as bet hedging may ensure the survival of its species within its host, heedless to the antibiotic.

Eukarya Edit

Eukaryotic bet hedging models, unlike prokaryotic models, tend to be used to study more complex evolutionary proceces. In the context of eukaryotes, bet hedging is best used as a way to analyze complex environmental influences affecting the selective pressures underlying the principle of bet hedging. However, because Eukarya is a broad category, this section has been subdivided into kingdoms Animalia, Plantae, and Fungi.

Vertebrates Edit

In example, West Atlantic salmon (Salmo salar) have been hypothesized to have major histocompatibility complex (MHC)-dependent mating systems, which have been shown in other species to be important for determining disease resistance among offspring. Namely, there is evidence that selection for increased MHC diversity is a strong influence on mate choice, where it is thought that individuals are more likely to mate with individuals whose MHC is less similar to their own in order to produce variable offspring. In accordance with the bet hedging model, it has been found that the reproductive success of mating pairs of Atlantic salmon is environmentally dependent, where certain MHC constructs are only advantageous under specific environmental circumstances. Thus, this supports the evidence that MHC diversity is crucial for the long-term reproductive success of the parents, as the tradeoff for an initial decrease in short-term reproductive fitness is mediated by the survival of a few of their offspring in a variable environment. [15]

A second example among vertebrates is the marsupial species Sminthopsis macrour, which use a torpor strategy in order to reduce their metabolic rate to survive environmental changes. Reproductive hormone cycles have been shown to mediate the timing of torpor and reproduction, and in mice have been shown to mediate this process entirely, heedless to the environment. In the marsupial species, however, an adaptive coin flipping mechanism is employed where neither torpor nor reproduction are affected by manipulation of hormones, suggesting that this marsupial species makes a more active decision about when to use torpor that is better-suited to the uncertain environment in which it lives. [16]

Invertebrates Edit

Many invertebrate species are known to exhibit various forms of bet hedging. Diaptomus sanguineus, an aquatic crustacean species found in many ponds of the Northeast United States, is one of the most well-studied examples of bet hedging. This species uses a form of diversified bet hedging called germ banking, in which emergence timing among offspring from a single clutch is highly variable. This reduces the potential costs of a catastrophic event during a particularly vulnerable time in offspring development. In Diaptomus sanguineus, germ banking occurs when parents produce dormant eggs prior to annual environmental shifts that yield increased risk for developing offspring. For example, in temporary ponds, Diaptomus sanguineus production of dormant eggs peaks just before the annual dry season in June when ponds levels decrease. In permanent ponds, dormant egg production increases in March, just before an annual increase in feeding activity of sunfish. [17] This example demonstrates that germ banking may take different forms within a species depending on the environmental risk presented. Bet hedging through variable egg hatching patterns are seen in other crustaceans as well. [18] [19]

Invertebrate bet-hedging has also been observed in the mating systems of some species of spider. Female sierra dome spiders (Linyphia litigiosa) are polyandrous, mating with secondary males in order to compensate for uncertainty regarding the quality of the primary mate. Primary male mates are considered to be of higher fitness than secondary males, as primary mates must overcome intrasexual fighting prior to mating with a female, while secondary male mates are chosen through female choice. Scientists believe multiple paternity has evolved in response to virgin insemination by low quality secondary male mates who have not undergone selection through intrasexual fighting. Females have developed a mechanism for sperm precedence to retain control over offspring paternity and increase offspring fitness. Further examination of female genitalia has supported this hypothesis. The sierra dome spider exhibits this behavior as a form of genetic bet hedging, reducing the risk of producing low quality offspring and contracting venereal disease. [20] This form of bet hedging is notably different than most other forms of bet hedging, as it has not arisen in response to environmental conditions, but rather it has arisen as a result of the species mating system.

Fungi Edit

Bet hedging is employed in fungi similarly to bacteria, but in fungi, it is more complex. This phenomenon is beneficial to fungi, but in some cases, it has harmful effects on humans, illustrating that bet hedging has clinical importance. One study suggests that bet hedging may even contribute to the failure of chemotherapy in cancer due to mechanisms similar to that of bet hedging used in fungi. [21]

One way fungi use bet hedging is by displaying different colony morphologies when grown on agar plates. [22] This variation allows for colonies with different morphologies, including resistances that allow them to survive, to thrive and reproduce in different conditions or environments. As a result, fungal infections may be more difficult to treat if bet hedging is involved. For example, pathogenic strains of yeast like Candida albicans or Candida glabrata using this strategy will resist treatments. These fungi are known to cause an infection known as candidiasis.

While bet hedging in fungi is important, not much is known about the mechanisms for the different strategies employed by different species. Researchers have studied S. cerevisiae to determine the mechanism of bet hedging in this species. [22] It was determined that in S. cerevisiae, variation exists in the distribution of growth rates among yeast micro-colonies and that slow growth is a predictor of resistance to heat. Tsl1 is one gene that was determined as a factor in this resistance. The abundance of this gene was shown to correlate with heat and stress resistance, and thus survival of the yeast micro-colonies under harsh conditions by using bet hedging. This illustrates that by using bet hedging, pathogenic strains of this yeast that are harmful to humans are more difficult to treat.

A group of researchers studied another way bet hedging is used by looking at the ascomycete fungus Neurospora crassa. [23] It was observed that this species produces ascospores with variation in their dormancy because non-dormant ascospores can be killed by heat, but dormant ascospores will survive. The only con is that it will take longer for the dormant ascopores to be germinated.

Plantae Edit

Plants provide simple examples for studying bet hedging in wildlife, allowing for field studies but without as many confounding factors as animals. Studying closely related plant species can help us understand more about the circumstances under which bet hedging evolves.

The classic example of bet hedging, delayed seed germination, [1] has been extensively studied in desert annuals. [24] [25] [26] One four-year field study [24] found that populations in historically worse (drier) environments had lower germination rates. They also found a large range of germination dates and flexibility in germination for drier populations when exposed to rain, a phenomenon known as phenotypic plasticity. Other studies of desert annuals [25] [26] have also found a relationship between temporal variation and lower germination rates. One of these studies [26] also found the density of seeds in the seed bank to affect germination rates.

Bet hedging through a seed bank has also been implicated in the persistence of weeds. One study [27] of twenty weed species showed that the percentage of viable seeds after 5 years increased with soil depth, and germination rates decreased with soil depth (although specific numbers varied between species). This indicates that weeds will engage in bet hedging at higher rates in circumstances where the costs of bet hedging are lower.

Collectively, these findings do provide evidence for bet hedging in plants, but also show the importance of competition and phenotypic plasticity that simple bet hedging models often ignore.

Archaea Edit

Thus far, research on bet hedging involving species in the domain Archaea hasn't been easily accessible.

Viruses Edit

Bet hedging has been used to explain the latency of Herpes viruses. The Varicella Zoster Virus, for instance, causes chickenpox at first infection and can cause shingles many years after the original infection. The delay with which shingles emerges has been explained as a form of bet hedging. [28]


Neuroscience

Neuroscience, the study of neuron and brain function, is among the most rapidly-expanding of biological disciplines. Neuroscientists in the Department of Molecular Biology focus primarily on systems, computational, and cellular questions, with an emphasis on the neural basis of learning and behavior. Specific projects address questions in visual processing, decision-making, social communication, working memory, spatial navigation, autism, and immune protein function in synapses. We ask these questions at levels ranging from single neurons and synapses to behaving animals.

Department neuroscientists use a variety of powerful technologies ranging from genetics and cell biology of model organisms such as mice, worms, flies to multi-photon imaging of neurons in action. A major strength of the community is the use of "NIH BRAIN Initiative"-style tools for manipulating and mapping brain circuitry. Examples of such methods include in vivo optical observation of brain activity using multiphoton microscopy detailed quantitative analysis of animal behavior computational analysis of complex data viral-assisted gene delivery to manipulate, monitor, and trace neural circuits the use and refinement of genetically encoded activity sensors and transgenic organisms. These tools are used to help understand how information in the brain is represented (neural coding) and changes over time (neural dynamics) to support complex behaviors. Neuroscience faculty in Molecular Biology are jointly appointed to the Princeton Neuroscience Institute, which houses the Bezos Center for Neural Circuit Dynamics, a center that focuses on the development and application of microscopy imaging techniques for measuring neural circuit dynamics in the functioning brain.


DeSantis C, Ma J, Bryan L, Jemal A (2014) Breast cancer statistics, 2013. CA Cancer J Clin 64(1):52–62

DeSantis C, Howlader N, Cronin KA, Jemal A (2011) Breast cancer incidence rates in U.S. women are no longer declining. Cancer Epidemiol Bio-markers Prev 20:733–749

Greaney ML, Sprunck-Harrild K, Ruddy KJ et al (2015) Study protocol for Young & Strong: a cluster randomized design to increase attention to unique issues faced by young women with newly diagnosed breast cancer. BMC Public Health 31(15):37

Villarreal-Garza C, Aguila C, Magallanes-Hoyos MC, Mohar A et al (2013) Breast cancer in young women in Latin America: an unmet, growing burden. Oncologist 18(Suppl):26–34. doi:10.1634/theoncologist.18-S2-26

Schmidt C (2015) Immunology: another shot at cancer. Nature 527(7578):S105–S107

Adams JU (2015) Genetics: big hopes for big data. Nature 527(7578):S108–S109

Eisenstein M (2015) Medicine: eyes on the target. Nature 527(7578):S110–S112

Reyna C, Lee MC (2014) Breast cancer in young women: special considerations in multidisciplinary care. J Multidiscip Healthc 29(7):419–429

Kroman N, Jensen MB, Wohlfahrt J, Mouridsen HT, Andersen PK, Melbye M (2000) Factors influencing the effect of age on prognosis in breast cancer: population based study. BMJ 320:474–478

Fredholm H, Eaker S, Frisell J et al (2009) Breast cancer in young women: poor survival despite intensive treatment. PLoS One 4(11):e7695

Hoag H (2015) Molecular biology: marked progress. Nature 527(7578):S114–S115

Lianos GD, Vlachos K, Zoras O (2014) Potential of antibody-drug conjugates and novel therapeutics in breast cancer management. Onco Targets Ther 24(7):491–500

Lianos GD, Roukos DH (2014) From linear ‘dogma’ and trastuzumab-emtansine to future transcriptional circuitry-based drug discovery for breast cancer. Future Oncol 10(2):145–148

Lee HB, Han W (2014) Unique features of young age breast cancer and its management. J Breast Cancer 17(4):301–307

Gabriel CA, Domchek SM (2010) Breast cancer in young women. Breast Cancer Res 12:212

Anders CK, Hsu DS, Broadwater G et al (2008) Young age at diagnosis correlates with worse prognosis and defines a subset of breast cancers with shared patterns of gene expression. J Clin Oncol 26:3324–3330

Jankowsk M (2013) Sexual functioning in young women in the context of breast cancer treatment. Rep Pract Oncol Radiother 18(4):193–200

Han W, Kim SW, Park IA, Kang D, Kim SW, Youn YK et al (2004) Young age: an independent risk factor for disease-free survival in women with operable breast cancer. BMC Cancer 4:82

Anders CK, Fan C, Parker JS, Carey LA, Blackwell KL, Klauber-De-More N et al (2011) Breast carcinomas arising at a young age: unique biology or a surrogate for aggressive intrinsic subtypes? J Clin Oncol 29:e18–e20

Chung M, Chang HR, Bland KI, Wanebo HJ (1996) Younger women with breast carcinoma have a poorer prognosis than older women. Cancer 77:97–103

Kim HJ, Han W, Yi OV, Shin HC, Ahn SK, Koh BS et al (2011) Young age is associated with ipsilateral breast tumor recurrence after breast conserving surgery and radiation therapy in patients with HER2-positive/ER-negative subtype. Breast Cancer Res Treat 130:499–505

Vitale SG, Valenti G, Gulino FA, Cignini P, Biondi A (2016) Surgical treatment of high stage endometrial cancer: current perspectives. Updates Surg 68(2):149–154

Rossetti D, Vitale SG, Gulino FA, Cignini P, Rapisarda AMC, Biondi A, Frigerio L (2016) Concomitant chemoradiation treatment in selected stage I endometrioid endometrial cancers. Eur J Gynaecol Oncol 37(5):657–661

Woodson AH, Profato JL, Muse KI, Litton JK et al (2013) Breast cancer in the young: role of the geneticist. J Thorac Dis 5(Suppl 1):S19–S26

Desmedt C, Yates L, Kulka J et al (2016) Catalog of genetic progression of human cancers: breast cancer. Cancer Metastasis Rev 35(1):49–62

Weisman PS, Ng CK, Brogi E et al (2016) Genetic alterations of triple negative breast cancer by targeted next-generation sequencing and correlation with tumor morphology. Mod Pathol 29(5):476–488

Azim HA Jr, Partridge AH (2014) Biology of breast cancer in young women. Breast Cancer Res 16(4):427

Stephens PJ, Tarpey PS, Davies H et al (2012) The landscape of cancer genes and mutational processes in breast cancer. Nature 486(7403):400–404

Azim HA Jr, Brohee S, Peccatori FA et al (2014) Biology of breast cancer during pregnancy using genomic profiling. Endocr Relat Cancer 21:545–554

Shuen AY, Foulkes WD (2011) Inherited mutations in breast cancer genes—risk and response. J Mamm Gland Biol Neoplasia 16:3–15

Huzarski T, Byrski T, Gronwald J et al (2013) Ten-year survival in patients with BRCA1-negative and BRCA1-positive breast cancer. J Clin Oncol 31:3191–3196

Weischer M, Nordestgaard BG, Pharoah P et al (2012) CHEK2*1100delC heterozygosity in women with breast cancer associated with early death, breast cancer-specific death, and increased risk of a second breast cancer. J Clin Oncol 30:4308–4316

Lianos GD, Zoras O, Roukos DH (2013) Beyond BRCA1/2: polygenic, ‘polyfunctional’ molecular circuitry model to predict breast cancer risk. Biomark Med 7(5):675–678

Copson E, Eccles B, Maishman T, Gerty S, Stanton L, Cutress RI, Altman DG, Durcan L, Simmonds P, Lawrence G, Jones L, Bliss J, Eccles D (2013) POSH Study Steering Group: prospective observational study of breast cancer treatment outcomes for UK women aged 18–40 years at diagnosis: the POSH study. J Natl Cancer Inst 105:978–988

Collins LC, Marotti JD, Gelber S, Cole K, Ruddy K, Kereakoglow S, Brachtel EF, Schapira L, Come SE, Winer EP, Partridge AH (2012) Pathologic features and molecular phenotype by patient age in a large cohort of young women with breast cancer. Breast Cancer Res Treat 131:1061–1066

Gnerlich JL, Deshpande AD, Jeffe DB, Sweet A, White N, Margenthaler JA (2009) Elevated breast cancer mortality in women younger than age 40 years compared with older women is attributed to poorer survival in early-stage disease. J Am Coll Surg 208:341–347

Keegan TH, DeRouen MC, Press DJ, Kurian AW, Clarke CA (2012) Occurrence of breast cancer subtypes in adolescent and young adult women. Breast Cancer Res 14:R55

Azim HA Jr, Nguyen B, Brohée S et al (2015) Genomic aberrations in young and elderly breast cancer patients. BMC Med 15(13):266

Azim H, Azim HA Jr (2013) Targeting RANKL in breast cancer: bone metastasis and beyond. Expert Rev Anticancer Ther 13:195–201

Ribnikar D, Ribeiro JM, Pinto D et al (2015) Breast cancer under age 40: a different approach. Curr Treat Options Oncol 16(4):16

Ademuyiwa FO, Cyr A, Ivanovich J, Thomas MA (2015) Managing breast cancer in younger women: challenges and solutions. Breast Cancer (Dove Med Press) 21(8):1–12

Bellia A, Vitale SG, Laganà AS et al (2016) Feasibility and surgical outcomes of conventional and robot-assisted laparoscopy for early-stage ovarian cancer: a retrospective, multicenter analysis. Arch Gynecol Obstet 294(3):615–622

Vitale SG, Valenti G, Biondi A, Rossetti D, Frigerio L (2015) Recent trends in surgical and reconstructive management of vulvar cancer: review of literature. Updates Surg 67(4):367–371

Freedman RA, Partridge AH (2013) Management of breast cancer in very young women. Breast 22(Suppl 2):S176–S179. doi:10.1016/j.breast.2013.07.034

Ferzoco RM, Ruddy KJ (2015) Unique aspects of caring for young breast cancer patients. Curr Oncol Rep. 17(2):1. doi:10.1007/s11912-014-0425-x

Verigos J, Magklara A (2015) Revealing the complexity of breast cancer by next generation sequencing. Cancers (Basel) 7(4):2183–2200

Martelotto LG, Ng CK, Piscuoglio S, Weigelt B, Reis-Filho JS (2014) Breast cancer intra-tumor heterogeneity. Breast Cancer Res 16(3):210

Desmedt C, Voet T, Sotiriou C, Campbell PJ (2012) Next-generation sequencing in breast cancer: first take home messages. Curr Opin Oncol 24(6):597–604

Rosa M (2015) Advances in the molecular analysis of breast cancer: pathway toward personalized medicine. Cancer Control 22(2):211–219

Roukos DH (2010) Novel clinico-genome network modeling for revolutionizing genotype-phenotype-based personalized cancer care. Expert Rev Mol Diagn 10(1):33–48


Christopher S. Fraser

Querido, J. B., Sokabe, M., Kraatz, S., Gordiyenko, Y., Skehel, J. M., Fraser, C. S., and Ramakrishnan, V. Structure of a human 48S translational initiation complex. Science. 2020 Sep 4369(6508):1220-1227.

Sokabe, M, and Fraser, C. S. Toward a Kinetic Understanding of Eukaryotic Translation. Cold Spring Harb. Perspect. Biol. 2019 Feb 111(2).

Avanzino, B. C., Fuchs, G., and Fraser, C. S. Cellular cap-binding protein, eIF4E, promotes picornavirus genome restructuring and translation. Proc Natl Acad Sci U S A. 2017 Sep 5114(36):9611-9616.

Sokabe, M., and Fraser, C. S. ATP-dependent restructuring of the 40S subunit decoding site during mRNA recruitment. Proc Natl Acad Sci U S A. 2017 Jun 13114(24):6304-6309.

García-García, C., Frieda, K. L., Feoktistova, K., Fraser, C. S., and Block, S. M. Factor-Dependent Processivity in the Human eIF4A DEAD-box Helicase. Science. 2015 Jun 26348(6242):1486-8.

Sokabe, M., and Fraser, C. S. Human Eukaryotic Initiation Factor 2 (eIF2)-GTP-Met-tRNAi Ternary Complex and eIF3 Stabilize the 43S Preinitiation Complex. J Biol Chem . 2014 Nov 14289(46):31827-36.

Özeş AR, Feoktistova K, Avanzino BC, Baldwin EP, Fraser CS. Real-time fluorescence assays to monitor duplex unwinding and ATPase activities of helicases. Nat Protoc. 2014 Jul9(7):1645-61.

Villa, N., Do, A., Hershey, J. W., and Fraser, C. S. Human eukaryotic initiation factor 4G (eIF4G) binds to eIF3c, -d, and –e to promote mRNA recruitment to the ribosome. J. Biol. Chem. 2013 Nov 15288(46):32932-40.

Feoktistova, K., Tuvshintogs, E., Do, A., and Fraser, C. S. Human eIF4E promotes mRNA restructuring by stimulating eIF4A helicase activity. Proc Natl Acad Sci U S A. 2013 110 (33) 13339-13344.

Sokabe M, Fraser CS, Hershey JW. The human translation initiation multi-factor complex promotes methionyl-tRNAi binding to the 40S ribosomal subunit. Nucleic Acids Res. 2012 Jan40(2):905-13.

Ozeş AR, Feoktistova K, Avanzino BC, Fraser CS. Duplex Unwinding and ATPase Activities of the DEAD-Box Helicase eIF4A Are Coupled by eIF4G and eIF4B. J Mol Biol. 2011: 412, 674-687

Fraser, C. S., Hershey, J. W., and Doudna, J. A. The pathway of hepatitis C virus mRNA recruitment to the human ribosome. Nat. Struct. Mol. Biol. 2009 Apr16(4):397-404.

Fraser, C. S., Berry, K. E., Hershey, J. W., and Doudna, J. A. eIF3j is located in the decoding center of the human 40S ribosomal subunit. Mol. Cell. 2007 Jun 2226(6):811-9.


16.4: Overview - Biology

A subscription to J o VE is required to view this content. You will only be able to see the first 20 seconds .

The JoVE video player is compatible with HTML5 and Adobe Flash. Older browsers that do not support HTML5 and the H.264 video codec will still use a Flash-based video player. We recommend downloading the newest version of Flash here, but we support all versions 10 and above.

If that doesn't help, please let us know.

The central dogma of molecular biology states that information encoded in DNA is transferred to RNA, which then directs the synthesis of proteins, based on these instructions.

First, in the process of transcription, DNA is used as a template to synthesize messenger RNA, mRNA, which represents a copy of the coding strand. Except the thymidines are replaced uracils.

Next, in the process of translation in eukaryotes, mRNA travels to a ribosome. Here, codons, groups of three nucleotides, in the mRNA, bind to complementary sequences on transfer RNA, tRNA molecules. Each of which is attached to a particular amino acid, depending on the specific codon.

For example, the codon CCA binds to a tRNA attached to proline, while AGC binds to a tRNA attached to serine. In this way, the genetic code specifies the order in which the amino acids are arranged in the resulting polypeptide. Polypeptides are often then further processed to become functional proteins.

14.2: The Central Dogma

Overview

The central dogma of biology states that information encoded in the DNA is transferred to messenger RNA (mRNA), which then directs the synthesis of protein. The set of instructions that enable the mRNA nucleotide sequence to be decoded into amino acids is called the genetic code. The universal nature of this genetic code has spurred advances in scientific research, agriculture, and medicine.

RNA Is the Missing Link between DNA and Proteins

In the early 1900s, scientists discovered that DNA stores all the information needed for cellular functions and that proteins perform most of these functions. However, the mechanisms of converting genetic information into functional proteins remained unknown for many years. Initially, it was believed that a single gene is directly converted into its encoded protein. Two crucial discoveries in eukaryotic cells challenged this theory: First, protein production does not take place in the nucleus. Second, DNA is not present outside the nucleus. These findings sparked the search for an intermediary molecule that connects DNA with protein production. This intermediary molecule, found in both the nucleus and the cytoplasm, and associated with protein production, is RNA.

During transcription, RNA is synthesized in the nucleus, using DNA as a template. The newly-synthesized RNA is similar in sequence to the DNA strand, except thymidine in DNA is replaced by uracil in RNA. In eukaryotes, this primary transcript is further processed, removing the protein non-coding regions, capping the 5&rsquo end and adding a 3&rsquo poly-A tail, to create mRNA that is then exported to the cytoplasm.

The Rules for Interpreting the mRNA Sequence Constitute the Genetic Code

Translation occurs at ribosomes in the cytoplasm, where information encoded in the mRNA is translated into an amino acid chain. A set of three nucleotides codes for an amino acid and these triplets are called codons. The set of rules that outline which codons specify a particular amino acid make up the genetic code.

The Genetic Code Is Redundant

Proteins are created from 20 amino acids in eukaryotes. Combining four nucleotides in sets of three provides 64 (4 3 ) possible codons. This means that it is possible that individual amino acid can be encoded by more than one codon. The genetic code is said to be redundant or degenerate. Often, but not always, codons that specify the same amino acids differ only in the third nucleotide of the triplet. For example, the codons GUU, GUC, GUA, and GUG all represent the amino acid valine. However, AUG is the only codon that represents the amino acid methionine. The codon AUG is also the codon where protein synthesis starts and is therefore called the start codon. Redundancy in the system minimizes the harmful effects of mutations. A mutation (i.e., change) at the third position of the codon might not necessarily result in a change of the amino acid.

The Genetic Code Is Universal

With a few exceptions, most prokaryotic and eukaryotic organisms use the same genetic code for protein synthesis. This universality of the genetic code has enabled advances in scientific research, agriculture, and medicine. For instance, human insulin can now be manufactured on a large scale in bacteria. This is done using recombinant DNA technology. Recombinant DNA consists of genetic material from different species. Genes encoding human insulin are joined with bacterial DNA and inserted into a bacterial cell. The bacterial cell performs transcription and translation to produce the human insulin encoded in the recombinant DNA. The resulting human insulin is used to treat diabetes.

Smith, Ann and Kenna Shaw. &ldquoDiscovering the relationship between DNA and protein production.&rdquo Nature Education 1 no. 1 (2008):112. [Source]

Ralston, Amy and Kenna Shaw. &ldquoReading the genetic code.&rdquo Nature Education 1 no. 1 (2008):120. [Source]


Watch the video: Animation What are the functions of our brain? (November 2022).