Clinical and pathological characteristics of giant cell angioblastoma: a case report

Rong-Jun Mao
Zhi-Ming Jiang
Hui-Zhen Zhang
Xiong-Zeng Zhu
Qing-Ling Zhang
Clinical and pathological characteristics of giant cell angioblastoma: a case report
C A S E R E P O R T Open AccessGiant cell angioblastomaBone tumorRare tumorPediatric malignanciesInterferon-α
Giant cell angioblastoma (GCAB) is an extremely rare soft tissue tumor of early childhood and only five cases have been described to date. As such the clinical, pathological, and prognostic features are poorly defined. We prensent here a new case of GCAB in bone of a child aged 4-years old. The lesion was composed of dense and loose cell regions. The dense regions were characterized by nodular, linear, and plexiform aggregates of oval-to spindleshaped tumor cells around small vascular channels and interspersed with large mononuclear cells and multinucleate giant cells. The loose cell areas were characterized by distributed fibroblasts and abundant myxoid matrix, which diminished with patient age. Infiltrative growth was observed in some areas. Oval-to-spindle cells showed positivity for Vimentin, CD31 and CD34 staining, and partial positivity for smooth muscle actin. Mononuclear cells and multinucleate giant cells showed Vimentin and CD68 positivity. Seventeen months after thorough curettage of the lesion, a local recurrence was found. Based upon the clinical, histological and immunohistochemical findings, infiltrate condition, and prognosis, we classified GCAB into two subtypes. Type I does not infiltrate surrounding tissues and has good prognosis. Type II infiltrates the surrounding tissues, relapses earlier, and has worse prognosis. This report augments the limited GCAB literature to promote our understanding and guide therapy of this rare disease. Virtual slides: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/ vs/6699811297488137

Background

Giant cell angioblastoma (GCAB) is an extremely rare soft tissue tumor of children. Diagnosis can be made according to the unique morphological characteristics, which include nodular, linear, and plexiform aggregates of oval-to spindle-shaped tumor cells interspersed with large mononuclear cells and multinucleate giant cells [1]. Since the first case of GCAB reported in 1991 [1], only one report described the other three cases of GCAB in infants occurring in the central palate, hypothenar portion of the right hand, and on the scalp, respectively [2]. We had reported the fifth case in the world of GCAB [3]. The involved tissues of GCAB in human pediatric patients have been reported as skin and soft tissue, including a substantial portion of an upper extremity [1], mucous membranes of the central palate, skin of the scalp, subcutaneous soft tissue of the right hypothenar eminence extending along the metacarpals [2], and leg bone [3]. Considering the extremely few case reports of GCAB worldwide, it is critical to include more case reports in the literature to increase our understanding of the clinicopathological features of GCAB. Here, we present the sixth GCAB case, which is quite different from the other five cases and occurred in the bone at the early childhood.

Iinterferon-alpha (IFN-α) has been successfully used as an antitumor therapeutic agent [4] and has shown robust antiangiogenic properties [5]. IFN-α has been used to treat two GCAB patients and showed remarkable wound healing properties after operative therapy, even promoting regeneration of bone [6].

A 4-year-old boy, who was born from a full-term healthy pregnancy, was presented with the complaint of unsteady standing since one-year-old. The symptom was worsened gradually with increasing restricted mobility of the right knee joint and a slowly enlarging mass on the inner side of the right lower thighbone and surrounding soft tissues. Examination found a 3 × 3 cm 2 relatively rigid mass with tenderness at the inner side of right knee. X-rays revealed that the medullary density of the right lower femoral metaphysis was irregularly reduced. CT imaging showed that the density of medullar of metaphysis was irregularly reduced and contained multiple small cysts. The cortex showed irregular thickening, and swelling was found in the proximal soft tissues. However, there was no obvious periosteum reaction ( Figure 1). A thorough curettage of the lesion was performed. However, seventeen months later, MRI examination revealed a local recurrence in the operated area.

Microscopically, the tumor occupied the medulla and eroded parts of the cortex, but the remaining bone trabeculae still displayed prominent osteoblastic rimming. The first characteristic noted in the case was the distinctive nodular histological feature, which was composed of oval-to-spindle cells and formed abundant vascular networks. The oval-to-spindle cells had congregated and circled to form a central vessel-like structure, which was filled with red blood cells. These oval-tospindle cells were considered likely to be the key of GCAB pathogenesis and had the ability to form a functional blood vessel within the tumor. The vascular endothelial cell markers-positive further confirmed that the oval-to-spindle tumor cells have the characteristics of vascular endothelial cells and pericytes. The second characteristic of GCAB was the abundance of mononuclear and multinucleate giant cells sprinkled throughout the tumor. The multinucleate giant cells and large mononucleate cells exhibited a distinctively strong expression pattern of CD68, which indicated a general histocytic lineage. The third characteristic of GCAB was the sparse presence of spindle-and spider-shaped cells, and mast cells, scattered throughout the loose mesenchyme of the tumor and accompanied by significant edema, myxoid or fibrosis in interstitial compartment. However, as this case was older than our former case (4years vs. 15-months) and the history of tumor-associated symptoms was longer, this characteristic was not obvious. Therefore, it might suggest that the oval-to-spindle cells have a tendency to proliferate and replace the regions of loosened mesenchyme or collagen over the pathogenic course of GCAB. In addition, widespread deposition of hemosiderins was observed and might be included as the fourth characteristic of GCAB ( Figure 2).

Immunohistochemical staining showed that most of the oval-to-spindle cells, large mononuclear cells, multinucleate giant cells, and periendothelial cells were strongly positive for vimentin, but uniformly negative for calponin, h-caldesmon, AE1/AE3, desmin, and CD1a. The perivascular cells of the vessels strongly expressed calponin and h-caldesmon. The monolayered small channels and oval-to-spindle cells in nodular or linear aggregate areas were positive for expression of vascular endothelial cell markers, CD31 and CD34, and partly expression of FVIII. SMA was most robustly expressed in

Differential diagnosis and prognosis

Histological differential diagnosis mainly involves other vascular neoplasms accompanying giant cell proliferation, such as giant cell fibroblastoma [7], angiomatoid fibrous histiocytoma [8], plexiform fibrohistiocytic tumor [7,9]. The giant cells in Giant cell fibroblastoma are characteristically located in the inner-side of the crannylike vasculature and CD34-positive, which is different from GCAB. Angiomatoid fibrous histiocytoma exhibits stretched tumor cells that are compartmentalized by cystic dilated vessel-like lumen, and have a compact envelope surrounded by abundant lymphocytes. Plexiform fibrohistiocytic tumors also form multiple nodulars, but lack vasculature and do not conform to hemangioma structures. The proliferated cells in plexiform fibrohistiocytic tumors are mononuclear histiocytes and fibroblasts. The osteoclast-like giant cells that sparked in the tumor lack clear, large nucleoli.

Intravascular lesions, such as reactive neoplastic lesions, with organized thrombus accompanied by central foreign material and an associated foreign body giant cell reaction should be carefully considered during diagnosis, and patient age and case history may help to distinguish the underlying disease [10]. In addition, as our case was derived from the tibia, it was important to rule out adamantinoma. Adamantinoma is characterized by biphasic epithelial and osteofibrous components and rarely occurs in children (median age at diagnosis: 25 to 35). Both of these features may be used to differentiate adamantinoma from GCAB [11]. Some of the malignant mesenchymomas, including leiomyosarcoma, rhabdomyosarcoma, chondrosarcoma, osteosarcoma and myxomatous components, should also be considered as differential diagnoses [12], and are distinguishable from GCAB by its lack of malignancy.

The prognosis of GCAB is not yet defined. Our follow-up to date has suggested that the prognosis of GCAB was relatively good but varied with site, patient age and the adjacent tissue infiltration. Tumor penetration of bone and infiltration of soft tissues might indicate early recurrence. And adjacent tissue infiltration would likely be the most significant marker for poor prognosis. Interferon-α therapy has been suggested as a preventative therapy against GCAB recurrence [2,6]. Neither of our two cases received IFN-α therapy, and the first case has shown no signs of recurrence within the three years of follow-up [3]. But this case recurred seventeen months after en bloc resection. Comparing the infiltrate condition of our two cases with all the other four reported cases led us to conclude that GCAB could be divided into two subtypes. Type I, as exemplified by our first case, occurs earlier, does not infiltrate surrounding tissues, and has good prognosis. Type II, as exemplified by the current case, occurs later and infiltrates the surrounding tissues, and is expected to relapse earlier and have worse prognosis. Type I could transform into Type II over long-term development. And IFN-α therapy may benefit for type II of GCAB.

Conclusion

Our newly identified case of GCAB supports that GCAB as a distinct and rare angiogenic tumor in infants with local infiltration potential. We summarized the six collective GCAB cases reported to date and distinguished them into two subtypes. Diagnosing and distinguishing the subtypes of GCAB is meaningful for estimating prognosis and guiding therapy. Infiltration status is likely a key prognostic indicator of GCAB. A definite diagnosis

Figure 1 X
1-ray and CT imaging of the right leg of the case. A. X-ray showed that the pattern of bone was generally normal and there was no swelling of surrounding soft tissue. Density of the metaphysis of the lower right thighbone had irregularly reduced. B and C. CT scan showed the density of medullar of the lower right femoral metaphysis was asymmetrically reduced with irregular thickening of the cortex and swelling of soft tissue. the perivascular cells of the well-developed vessels and monolayered small channel in the hemangioma-like areas. Other regions of the tumor showed weak or no staining for SMA. The large mononuclear cells and multinucleate giant cells exhibited strong expression of the classic macrophage marker, CD68, but negative for Desmin, S-100, LCA, and SMA (Figure 3).

Figure 2
2Microscopic features of the case. A. The tumor formed by dense and loose cell regions. The dense regions were composed of plexiform and nodular oval-to spindle-shaped tumor cells. The loose regions were composed of fibrosis. Bone trabeculae erosion was observed. B. There were relatively clear boundaries of dense and loose cell regions, both of which exhibited abundant capillary vessels. Muscle infiltration was confirmed by the few residual muscle cells in the tumor (arrow). C. The loose region was made up of two components. One was a fibrotic area with fibrinoid degeneration, and the other was composed of sparse stellate-shaped cells with myxoid background. D. The large mononucleate cells and multinucleate giant cells were randomly-distributed among the oval-to-spindle cells, with abundant capillary vessels in the mesenchyme. The osteoclast-like multinucleate giant cells were abundant and scattered randomly. E. The oval-to-spindle cells and giant cells aggregated to form non-necrotizing-like granulomas lesions, with abundant small vascular-formation. F. The sponginess hemangioma regions were also observed in the dense tumor cell nodules. G. The thick-wall vessels with periendothelial proliferation were congregated in some areas. This pattern always appeared in the loose region. H. The big vessels showed periendothelial proliferation and protruding into the lumen, as well. Stellate-shaped cells were sporadically distributed in the loose region. I. The big thin type of vessel was seen in some areas. (H&E stain. Magnification: A: 10×, B-I: 40×).

Figure 3
3Immunohistochemical staining of GCAB. A. Vimentin-positivity throughout the tumor. B. SMA-positivity in perivascular cells of the well-developed vessels and basement membrane. C. CD68-positivity was strong in the giant cells, weak in some oval-to-spindle tumor cells. D. CD34-positivity in the oval-to-spindle tumor cells and the monolayered small channels, but not in the giant cells. (Magnification: A, B, and D: 40× C: 20×).
http://www.diagnosticpathology.org/content/7/1/113
followed by complete excision might facilitate better prognosis of GCAB. Interferon-α therapy benefits type II GCAB patients.ConsentWritten informed consent was obtained from the patient for publication of this Case Report and any accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.Competing interestsThe authors declare that they have no competing interests.
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Clinical and pathological characteristics of giant cell angioblastoma: a case report. Mao, Diagnostic Pathology. 113Cite this article asCite this article as: Mao et al.: Clinical and pathological characteristics of giant cell angioblastoma: a case report. Diagnostic Pathology 2012 7:113.


ON THE ECONOMICS OF HAPPINESS: THE INFLUENCE OF INCOME AND NON-INCOME FACTORS ON HAPPINESS

Darma Mahadea
School of Accounting, Economics and Finance
University of Kwazulu-Natal

ON THE ECONOMICS OF HAPPINESS: THE INFLUENCE OF INCOME AND NON-INCOME FACTORS ON HAPPINESS
DCC951DCA9380FCA646FEEA09E8D088DAccepted: October 2012subjective well-beingeconomic growthincomedebthappinessdebtrelationships JEL: D1E2I3J1
The quest for individual happiness and a better life for all is an important economic objective in countries as different as South Africa and France or Zimbabwe and Bhutan.Economists have focused attention on the effects of consumption, income and economic growth or development on well-being and whether economic growth can be the sole basis for delivering prosperity (Dutt & Radcliff, 2009; Jackson, 2010).The search for happiness is an important individual and national economic goal.In the Benthamite utilitarian tradition, happiness is the sum of all pleasures and pains.People often obtain or perceive their happiness from what they have in comparison with others.At the macroeconomic level, more happiness may come from a sustained growth in GDP that enables households to enjoy an improved quality of life, with rising income, consumption and employment opportunities.At the microeconomic or individual level, more income may also enable people to live happier and fuller lives relative to those who are poor.But this accounts for only a small contribution to happiness.Life circumstances, such as marital status, health, having children and the nature of the working environment statistically make a greater contribution to happiness than income.

Introduction

"In my view, the prime purpose of social science should be to discover what helps and what hinders happiness." (R. Layard)

The quest for individual happiness and a better life for all is an important economic objective in many countries as diverse as South Africa and France or Zimbabwe and Sweden.All of us want to be happy and lead more fulfilling lives, but not everybody is happy.In former times, happiness was studied mainly by philosophers and psychologists.In recent years, though, happiness has been a topical subject in Economics too.The Economic Journal states: "Economists from different backgrounds …. all believe that happiness must play a more central role in economic science again" (Dixon, 1997(Dixon, :1812)).Psychologists are examining happiness through brain signals, personality traits and environmental factors.Philosophers have probed happiness by looking at the maximization of pleasure and the minimization of pain, and virtuous life qualities.Some social scientists consider the effects of friendship, family, communities and groups on happiness.Economists have focused on the influence of consumption, income and economic growth or development on well-being, and are debating whether economic growth can be the sole basis for delivering prosperity, and whether income buys happiness (Dutt & Radcliff, 2009;Jackson, 2010).It is popularly believed that happiness increases when people consume more goods and services with rising income.

Many individuals seek happiness by acquiring wealth, or working long hours to make money, often at the expense of leisure and good social relations.They believe that happiness lies in material possessions, through the satisfaction of material desires.Income is earned primarily through employment.The more income individuals can earn, the more goods and services they can afford to buy and the more satisfaction they can enjoy.In utilitarian theory, more income is better, as it enables individuals to maximize utility through a greater demand for goods and services.At the national level, the aggregate annual value of final goods and services Abstract produced in the country is its GDP, which serves as a basis for measuring economic growth.

More goods being produced entails more demand for labour, more employment and more income generation to buy the goods and services produced.As economic growth increases real per capita income, people can afford to buy more goods and services.This, in turn, may result in enhanced well-being and subjective happiness.It is thus no surprise that certain former and current top policy-makers, such as Nicholas Sarkozy and David Cameron, support the measurement of national wellbeing or happiness rather than GDP (Porter, 2011).

Economic reasoning would suggest a positive relationship between income and happiness.Empirical studies suggest that higher income resulting from high rates of economic growth contribute to poverty alleviation and greater life satisfaction in low income countries (Layard, 2007).Higher income raises the happiness of the poor at a point in time and place.In developed countries, a higher income does not seem to 'buy' greater happiness over time, once a threshold level of income is reached (Easterlin, 2001;Frey & Stutzer, 2002;Layard, 2006).As the study of happiness gains a wider perspective, other factors, such as social capital (relationships) and human capital (education) are emerging as key determinants of subjective well-being.Does income contribute to happiness in a developing country?If increases in income and consumption do not make people significantly happier, at least beyond a certain level, what economic choices and environmental conditions do?This exploratory study examines the influence of income and non-income factors on happiness.

Literature review on happiness

In order to enhance the happiness of members of society, one needs an understanding of 'happiness' and the contributing factors.

Happiness is an elusive concept, which is not defined in a definite way in the literature (Porter, 2011).Classical economists argue that more wealth is just a means of being happy (Smith, 1759:166), and 'to increase the wealth of a state tends also, generally speaking, to increase happiness' (Malthus, 1798:303).Veenhoven (1993) defines happiness as the degree to which an individual judges the overall quality of his or her life as being favourable.Recent studies show that happiness increases with income and entire nations could be happier with an expansion in economic growth (Veenhoven & Hagerty, 2006:21).The traditional economic view is that 'more is better.'So as GDP per capita increases, consumption rises, and so does aggregate wellbeing.Ng (1997) argues that at the micro level, each of us wants money, not for its own sake, but for what it can bring us in terms of happiness.

Economics has traditionally viewed happiness in terms of subjective well-being.In terms of economics, happiness takes reported subjective well-being as a proxy for utility (Frey & Stutzer, 2002).Ng (2006) defines happiness as 'welfare', while for Oswald (1997), happiness means hedonistic 'pleasure' or 'satisfaction'.Layard (2011) regards happiness as enjoying life and feeling good, and is thus synonymous with subjective well-being (SWB).Individuals are said to have high SWB if they experience high-life satisfaction and frequent pleasant emotions such as joy and affection, and only infrequently experience unpleasant emotions.Easterlin (2001:465) views happiness from a broader perspective: "I use the terms happiness, subjective well-being, satisfaction, utility, welfare interchangeably".

According to the Utilitarian and Benthamian philosophy, the individual's conduct and government policies should be directed toward promoting the greatest happiness for the greatest number of people and minimizing pain, enabling a rightward shift in the social welfare function.Bentham's 'greatest happiness principle' is universal.In his 'Theory of Moral Sentiments', Smith (1759:232) postulated that leaders should "secure the internal tranquility and happiness" of their fellow-citizens.

Research indicates a link between happiness and income.People with higher incomes have a higher status in society, which intrinsically makes them happy and enables them to enjoy positional goods.These are exquisite and expensive goods that are scarce in some absolute or socially imposed sense, subject to crowding through extensive use.In this sense, "income does buy happiness" (Frey & Stutzer, 2002:40).High income earners can augment their own happiness and that of poorer people too through their altruistic actions and donations of money to charitable organizations (Black, Calitz & Steenkamp, 2003).The marginal significance of a Rand gained in utility to the poor is more than a Rand lost in utility to the rich.Happiness has a positive contagion or externality effect, as individuals with high income can make other people happier just by being happy themselves.

The behavioural school, in particular Daniel Kahneman, the Nobel Prize winner for Economics in 2002, treats happiness as a subjective issue that is measurable through surveys.This is made possible by asking respondents, for example, how happy they are on a scale (1 to 10), at a given moment and over time (Layard, 2006).Frey and Stutzer (2002:405) argue that, in evaluating happiness in relation to income and other factors, it is sensible in Economics to rely on the judgments of people as they are thought to be the best judges of the overall quality of their own lives.Stutzer (2001:37) asserts that the measures of subjective well-being have a "high consistency, reliability and validity", as well as a high stability over time (Konow & Earley, 1999).

Income and happiness paradox

At any given time, richer people claim to be happier than poorer people.In developing countries, higher income raises the happiness of poor people living below the bread line.In developed and richer countries, higher income does not seem to 'buy' higher happiness, once a threshold level of income has been reached.Several studies show that, on average, individuals in wealthier countries are happier than those in poorer countries, and there is a significant relationship between happiness and income at a particular point in time and in a given country (Oswald, 1997;Frey & Stutzer, 2002:10).

Although real income per head has increased significantly in developed countries, like America, Japan and Europe, studies using data from the past five decades, have indicated that people there, on average, are currently no happier than in earlier times (Layard, 2011).This suggests that happiness levels fail to rise significantly as rich countries become even richer.This seems like a paradox.Easterlin (2001) argues that absolute income matters to individual happiness up to a point, but once basic needs have been met, relative income matters more for happiness.People compare their incomes and style of living with those of others in the income distribution.Raising everyone's income does not raise everyone's happiness because, in comparison with others, income has not improved (Easterlin, 2001:481).

Individuals seeking more income to increase their happiness are unlikely to be satisfied, as they aspire to getting more and more.As they earn higher income, their aspirations change.They feel dissatisfied with what they have and they may wish to possess more material goods and indulge in conspicuous consumption, possibly by contracting debt.The lack of satisfaction with what individuals currently have and their need to emulate the habits of celebrities or others, partly because of consumerism, and trying to "keep up with the Joneses" prompt them to buy more.Although many catch the 'luxury fever', this 'affluenza' and status do not necessarily make them permanently happier (James, 2007;Frank, 1999).

While these status competitions and consumption patterns increase material throughput (Jackson, 2010), they can make individuals vulnerable to depression, anxiety, substance abuse and personality disorders, all of which detract from happiness (Wilkinson & Pickett, 2010).Further, while more income resulting from economic growth can lead to more comfort, increased choices and richer lives, this may also lead to less stimulation and more disparities, possibly contributing to a "joyless society" (Scitovsky, 1992;Jackson, 2010).

As people buy more on credit, and consume more, they do not save enough and their level of debt increases.High levels of outstanding debt, other than home mortgaged debt, can reduce their happiness (Dutt, 2008).This debt would be an added burden in their lives, if credit were taken simply for consumption motives.It is partly against this background that the National Credit Act was introduced in South Africa in June 2007 as a way of protecting consumers from accumulating high debt that they cannot afford.However, debt may not necessarily be an impediment to happiness if it is directed towards investment with a potential for generating higher income.Increased debt, in this instance, could actually enhance happiness when the investment payoffs lead to increased financial security.

Non-income influences on happiness

Individuals earn an income primarily from supplying their labour services and talents to the market.People with more education are generally more productive and earn more; they tend to be happier than those with less education.Hinks and Gruen (2007) found that South Africans with tertiary education are happier than those who have no education.

Research indicates that people with more capabilities and freedom, tend to earn more income and, are happier than those with fewer skills; individuals in democratic societies are happier than those who live under repressive regimes (Sen, 2010).Living in an environment of economic and social security has a powerful impact on an individual's well-being (Inglehart, 2009).The quality of the relationships one has at work, in the community and in the family environment has a bearing on individual happiness.Individuals with better family ties, with children and friendships and a good working environment, are happier than others for whom these qualities are lacking.Thus, social capital impacts on the well-being of the individuals (Dutt & Radcliff, 2009).

Social connectivity keeps individuals less isolated, better supported, more bonded and thus happier (Putman, 2001;Lane, 2000).Further, people who have good health and who are more extroverted are happier than others.The happiest group tends to experience generally positive feelings (Diener & Seligman, 2002).Intrinsic religious commitment tends to have a positive effect on life satisfaction as it often promotes virtuosity, spirituality and the values of caring concern for others and mankind (Hamilton, 2004).Further, married people tend to be happier than those who are single, divorced or widowed (Oswald, 1997;Layard, 2006).Powdthavee (2007) found that South Africans in civil marriages are significantly happier than people who are single and have never married.In short, Layard (2011) identifies seven factors influencing happiness.Listed in order of 'importance', these are: family relationships, financial situation, work, community and friends, health, personal freedom and values.

Although South Africa is at a medium level of human development (ranked 123 rd out of 187 countries), its perceived overall life satisfaction index over the period 2006-2010 stands at 4.7.This is below the average of the same development group, 4.9, and below the global average figure (5.3) (Human Development Report, 2011).However, according to the World Database of Happiness, South Africa had an average level of happiness or life satisfaction of 5.8 over the period 2000-2009.Life satisfaction is based on a scale of 1 (dissatisfied) to 10 (most satisfied).The average level of happiness, as measured by the World Value Survey question: "All things considered, how satisfied or dissatisfied are you with your life as a whole these days?",actually decreased from 6.8 in 2006 to 6.31 in 2007 and to 4.95 in 2008 (Veenhoven, 2012).This clearly shows that people in South Africa have been experiencing, on average, a reduced level of life satisfaction in recent years.This may arise partly because of high levels of unemployment, poverty and inequality (Vavi, 2011).

Economic growth and income growth in South Africa

Income and its increase matter a great deal to happiness when people live in poverty.Over the past 17 years, since the dawn of democracy in South Africa, the country has consistently registered positive economic growth rates, as high as an average rate of 5.

Sample particulars

This study explores the relationship between the level of income and happiness, in the form of a survey carried out in the greater Durban region of South Africa.A questionnaire was used to gather data on the respondents' selfreported level of happiness on a Likert scale 1 (least happy) to 5 (most happy) and their socioeconomic attributes.The question on selfreported happiness has evident face validity.It clearly addresses happiness, as defined even in the World Database of Happiness.Previous research has also shown high internal validity as expressed in consistency of responses to this similar question: 'Taking all things together, how would you rate your quality of life/level of happiness?(Layard, 2011;Veenhoven, 1997).This suggests a subjective appreciation of life.It is the subject who makes the appraisal of their subjective well-being or happiness and who is the best judge of their true level of life satisfaction.

Respondents had to self-rate their happiness on a multi-item questionnaire and scale.Researchers need to gather information on different life domains to understand what makes for happiness (Veenhoven, 1997).Accordingly, the questionnaire, administered in face-to face interviews, also sought information on the respondents' income, education, types of debt, and demographic background.All these variables were treated as categorical factors.Questions relating to their health, work environment, debt, friendships, and religion were measured on a ten-point Likert scale, enabling respondents to indicate their opinions on how strongly each factor influenced their personal happiness.Respondents were requested to rate the extent to which the latter variables contributed to their personal happiness, on a 1 to10 scale, with low values reflecting "no" or " low importance" and the highest value (10) indicating most important.Reliability is the consistency of a questionnaire and can be reflected by the Cronbach's alpha.In this case, the Cronbach's alpha was just under 0.7.Although values in the Cronbach's alpha greater than 0.7 are seen as indicating a good overall reliability, a slightly lower value is acceptable (Coakes & Steed, 2003).

The data was analysed by using SPSS.The sample was chosen by random selection.The sample size is rather limited (n=220) owing to resource constraints, but it is proportionally drawn according to the population dynamics of the region.The small sample and its exclusive focus on the Durban region is a limitation of the study.Nevertheless, certain pointers to happiness are discernible, though a larger sample covering more regions, and variables with intermediating influences, and stronger statistical approaches may be preferable for future research.

The sample consisted of 151 black, 45 Indian, 18 white and 6 coloured individuals.There were 114 female and 106 male respondents.Of the sample, 151 were single, 61 married, 6 divorced and 2 widowed.As far as age was concerned, 120 were in the 18-30 group, 74 in the 31-45 group, 21 in the 46-60 group and 5 were retired.The aim of the study was to capture the quantitative and qualitative sources of happiness, then consider whether non-income factors are more important than income in contributing to happiness and examine whether happiness varies with gender.

Methodology and results

Initially, the surveyed variables, education, number of children, debt and gender, as independent factors, and happiness as the dependent factor, were fitted into a multiple regression analysis, and they were all found not to be significant, except for income.As a result, only income and happiness are used in the analysis.The methodology thus used is the GLM regression analysis, in which the level of (self-reported) happiness (H) is the dependent factor, income is (Y), a is the intercept, b is partial regression coefficient of the independent factor, and e is the error term, expressed in the equation below.

Consistent with other studies (Powdthavee, 2011;Layard, 2007), happiness was examined along a continuum, from least happy (1) to most happy (5).Income was measured along a continuum from low (R1000) to high (R18000 and above).Both variables were treated as continuous variables (Powdthavee, 2011).The GLM method was used because the dependent variable in the regression is non-normal; accordingly the conventional regression may not work.A regression approach was also used by Hinks and Gruen (2007) and by Powdthavee (2007) in their studies on happiness in South Africa.

Thereafter, a factor analysis and a principal component analysis with a Varimax rotation were undertaken.The factor analysis was similarly used by Heukamp and Arino (2011) in their study on the subjective well-being of different characteristics in various countries.The usual chi-square test is used to examine the association between gender and types of debt and t-test to examine the differences in happiness between the male and female group.The results are presented in two stages.Initially the descriptive findings are presented, after which they follow the regression results.Finally, there is a discussion of the findings of the factor analyses.

Descriptive results

The study found that the majority of the people surveyed were happy.Only 4.1 per cent reported being "not happy at all"; 8.2 per cent reported "not being very happy", 36.4 per cent reported being "fairly happy" and 33.2 per cent reported being "very happy" and another 18.2 per cent reported being "extremely happy".

The gross monthly income of the respondents ranged from R1000 to R18000 and more.In the low income group R1000-2000, there were 31.4 per cent of the respondents, 26.8 per cent were in the R2001-R4000 group; 19.1 per cent were in the R4001-R8000 group and 22.7 per cent in the R14001 -R18000 and more group.

Regarding the education of the respondents, 8.6 per cent had a low level of education, between Grades 4 and 11, 57 per cent had Matric, 30.5 per cent had a university degree or tertiary education and about 4 per cent had a postgraduate education.

The effect of gender on happiness was examined by comparing the mean happiness levels of women (n=114) and men (n=106) in the sample.Women reported a mean happiness level (3.61) marginally higher than that of the men (3.44).However, the difference was not found to be statistically significant (p = 0.492).This result is similar to that of Hinks and Gruen (2007).

Married people are reportedly happiest, with a mean happiness score of 3.61.Single people had a mean happiness score of 3.51, divorced people had a mean happiness of 3.50 and widowed people had an average happiness score of 3.

When it came to debt, 27 per cent of the respondents reported that they did not use credit.Among those who contracted debt, female respondents used more credit cards only (14.9 per cent) than did males (8.5 per cent), had more car loans only (1.8 per cent) than did males (0.9 per cent) and had more instore accounts only (31.6 per cent) than males did (22.6 per cent).The Chi-square test indicated that there was a significant association between gender (being female) and types of debt (X 2= 18.56; p= 0.046).

Regression results

The regression results show that income is a significant predictor of happiness (R-Square = 0.057; p= 0.013, F= 3.234).Despite this, the explanation is rather weak, claiming only about 6 per cent of the variation in happiness.But finding a weak connection between income and happiness is similar to other studies on happiness in the literature (Frey & Stutzer, 2002;Ng, 2006;Biswas-Diener, 2007;Mahadea & Rawat, 2008).In effect, typical studies in developed countries, and even those using more sophisticated multilevel analysis, have found that, at most, income explains only about 2-4.5 per cent of the difference in happiness between individuals (Saris, 2001;Hsieh, 2004;Ahuvia, 2012).According to set point theory, people have a natural level of happiness that is set largely by their genetics and personality.However, there may be occasional departures from the mean point, for instance when there is a lottery win or positive exogenous event, but the average level reverts to the equilibrium set point soon afterwards.About 50 per cent of the variance in subjective well-being is apparently genetically determined, and the remainder may be accounted for by intentional activities, i.e what the people do for good or ill, and by circumstances (Sheldon & Lyubomirsky, 2009).As income is found to be explaining only a small proportion of the variation in happiness, one is interested in other possible factors that could be associated with subjective well-being.This prompted us to use factor analysis.However, it must be pointed out the factor analysis is not about causality; it is about finding groupings of similar variables that are correlated into principal component groups, related in this case to happiness.

Factor analysis

To capture the influence and significance of other non-factors on happiness, a factor analysis and a Principal Components analysis with Varimax Kaiser normalization is undertaken.The factor analysis is used to reduce a large number of variables to a smaller set of underlying factors that can explain happiness.The principal component analysis decomposes the original data into a set of linear variables and shows how a particular variable might contribute to that component (Field, 2009).This approach is suitable because it takes into account unobserved variability in the measured variables.This in turn gives us the most influential factors affecting happiness.

A set of seven factors with Eigen values greater than 1 emerged as key clusters influencing happiness.The first component, consisting of two factors, has an Eigen value of 2.022, and it explained 14.4 per cent of the variation in happiness (Table 1).The two factors of substantive importance influencing happiness are marital status and the number of children (Table 2), with a weight of 0.828 and 0.822 respectively.The second set has three factors (health, working environment, and religion with loadings 0.809, 0.731, 0.570 respectively).This component has an Eigen value of 1.805, and it explained 12.8 per cent of the variation in happiness (Table 1 and Table 2).Of these factors, health and the work environment are found to have a greater influence on happiness than religion does.People who are healthier and have a positive work environment are less prone to sickness and appear to be happier than others.People who are religious perhaps suffer from fewer health risks and this combines with their work environment and thus contributes to their happiness.Indeed, this partially supports Rule's (2007) study in South Africa, which found that religious importance positively affects happiness.Thus, individuals who practice a religion may have a higher level of happiness than those who do not follow any religion.The third component, consisting of two factors (income and education, with weightings of 0.782 and 0.764 respectively) explained 10.2 per cent of the variation in happiness (Table 1  and 2).Both factors are almost of equal importance in influencing happiness, as their weights are nearly equal to each other.Better educated people tend to be more productive and earn a higher income, and hence tend to be happier in comparison with their counterparts with low education or income.Thus, as human capital influences an individual's earnings, it can also influence happiness.Income differences influence happiness; this possibly led Frey and Stutzer (2002:10) to argue that income does buy happiness.Individuals with lower income levels find a significant difference in their current level of happiness relative to those in the higher income group.The influence of debt and friendship on subjective well-being was also examined.A rather surprising result emerged from the association between debt and happiness.These two factors belong to the fourth cluster and explain nearly 10 per cent of the variation in happiness.From Table (2), given that level of debt and friendship are found to be in the same component, it appears that one's friendly relationships with others are perhaps associated with the level of debt.As this is an unexpected result, the relationships between debt or ethnic patterns of debt and happiness is an area that requires further research with a qualitative and interactive approach.However, the case of consumer debt is interesting, as at any given level of income, increased debt may reflect increased consumption that may arise from easier access to credit.Perhaps this has a demonstration effect (Dutt, 2008), in that people who have more friends might contract more debt or rely on friends for loans.People often contract debt to impress others, to enhance consumption and to have access to durables because others do (Duesenberry, 1949) and thus tend to be happier.However, more debt can also be associated with reduced savings and less happiness.

Younger people tend to be less conservative and are more likely to contract debt; this may influence their happiness level.Age and how people feel about debt explain almost 9 per cent of the variation in happiness.Different ethnic groups tend to gravitate to certain types of debt.Hence, types of debt and the ethnic groups are in the same component, jointly explaining just over 7 per cent of the variation in happiness (Tables 1 and 2).

The last factor is gender, with a weighting of 0.880, accounting for about 7 per cent of the variation in happiness.Jointly, all the above factors explained about 70 per cent of the variation in happiness.However, the first three components are of greater relative significance, as about 50 per cent of the variation in happiness is explained by social relationships, human capital and income.Diener and Seligman (2002) also found that social relationships, through satisfying family life, marriage and friendship, are most important for high happiness.In contrast, Perkins (1991) found that individuals who prefer high incomes, which accompany occupational stresses, to the detriment of close friendships and marriage describe themselves as unhappy.Overall, married people with education and children are found to be happier than others, but there is no significant difference in happiness between males and females.

Recommendations

There is no sole determinant that exclusively explains overall subjective well-being.The small sample size is a limitation to this study.However, on the basis of certain pointers, which correlate with those of other studies of a larger sample size, certain tentative recommendations many be inferred.But these suggestions are to be treated with care, owing to the data limitations of the study.As inferences are drawn from a small sample, the results cannot be generalized.Income has a relatively small influence on happiness.Higher income may enable an individual to buy material goods that have direct tangible benefits on subjective well-being, but material possessions do not contribute to lasting happiness.Improvements in income can make people happier for a while, but the effect fades rapidly, as aspirations change over time and people are habituated to different environmental settings.Although money is not everything to happiness, the acquisition of money can become an obsessive life-goal.The individual does not seem to be satisfied with what he has.He is concerned with more material needs, which increase with higher income.

Different conditions, mediating factors and outcomes make different people happy.The quality of life and relationships is critical for happiness and wellness, rather than just income.At the individual level, friendship and marriage have a profound positive effect on happiness, through companionship, and financial and emotional security, whereas separation dissolves a relationship (Ahuvia, 2012;Layard, 2011).As Nobel Prize Winner, Gary Becker (1993) argues, marriage enables the husband and wife or partners to be specialized producers of complementary household goods and services that enhance life satisfaction, and, by staying together, they profitably provide communal goods and services that further enhance happiness.One cannot be happy in isolation.People can enhance their happiness and life satisfaction if they can try to devote more time and energy to building family, friends and social networks that promote well-being.As Lane (2000) puts it, it is friendship and other social connections with other human beings that are important contributors to a rewarding and happy life.Marshall (1890:2) argued that "in religion, in the family affections and in friendship, even the poor may find scope for….the highest source of happiness".

Time is a critical finite resource that can be spent on production (work) and consumption (leisure).More time spent at work implies less leisure time.It is understood that, at certain times, people may have to work long hours for purely financial reasons.There are social pressures to work more and engage in status consumption that provides temporary satisfaction, often with debt creation, which may be too strong to overcome individually.While more money can be earned through spending more time at paid work, this could be to the detriment of social and family relationships.A balance in allocating one's time between work and leisure is therefore desirable, so that 'quality' time can be spent on looking after one's health and building up and nurturing social relationships that result in higher levels of happiness and a better quality of life.Wilkinson and Pickett (2010:274) put it succinctly: "It is family, friends and community that matter to happiness".Jackson (2010:16) reinforces this point, arguing that happiness goes beyond material pleasures; it resides in the quality of our lives, in the health and wellbeing of our families, in the strength of our relationships and our trust in the community within the ecological limits of a finite planet.He suggests an alternative hedonism -a downshifting lifestyle over time for individuals where the emphasis is on simplicity.This is possible through devoting less time to material pursuits and greater time to gardening, walking, music, reading and the care of others, thus pursuing a way of living that is outwardly simple yet inwardly rich (Jackson, 2010:149).

As income is gained mainly from work, and considerable time is spent at work, employers can play a role in influencing happiness and hence the employees' productivity.If employees are satisfied with their jobs and work in a positive or fulfilling environment, they can become happier.Stress at work can invade the family environment.It is therefore in employers' interests to ensure a healthy working environment, as happier workers are more productive and absent themselves less frequently from work.This could contribute to greater profits for the firm for which they work.Employers may obtain better productivity by refining the internal work environment rather than improving pay.Thus, although income does not buy happiness, happiness can save income.

Health and education are also found to be associated with well-being.It is therefore suggested that policymakers should implement measures that allow for adequate access to health care and education for all citizens, enabling them to enjoy a better quality of life.The expansion of capability and empowerment through education is invariably welfareenhancing and augments human happiness (Sen, 2010:286).Increased access to education would also help to narrow South Africa's high levels of inequality by reducing the divergence of wealth and opportunities in the country.Societies with more trust and less inequality have fewer crimes and thus are happier (Wilkinson & Pickett, 2010;Powdthavee, 2011).In the case of South Africa, Powdthavee (2011) found that crimes have a greater adverse effect on happiness than unemployment does.

Debt may not necessarily be a limitation to happiness, if it is entrepreneurially used to finance income generation activities and meet basic needs for shelter.Loans for activities that pay for themselves can raise the wealth and financial security of individuals.Hence debt instruments that finance income generating investments rather than consumption are to be supported, as they can lead to their holders attaining a higher level of happiness, and possibly reducing stress in their lives.

At the national level, people could be happier if there were more opportunities for them to gain an income through value-adding activities in the labour market rather than through transfer payments, in the form of social grants.This entails job creation, which could increase with economic growth.Studies conducted in other countries clearly show that unhappiness stems from unemployment (Oswald, 1997;Layard, 2011;The Economist, 19/2/11).Creating new jobs is essential for a renewed sense of well-being and national prosperity.Growth with employment could alleviate poverty, as people could earn higher incomes and gain self-esteem, allowing them to obtain more goods and services, and to lead a better and happier life.

Conclusion

The search for happiness is an important individual and national economic goal.At the macro level, more happiness may come from a sustained growth in GDP that would enable households to enjoy an improved quality of life, with rising income and employment opportunities, as well as fiscal redistribution.Individuals earn an income mainly from employment.The higher the level of income the more utility could be gained from consumption and the more satisfied a person would be.Having wealth may give an individual a sense of security, recognition and affordability.More income may also enable people to live happier and more fulfilled lives relative to those who are poor.But income accounts for only a small contribution to happiness.

Life circumstances, such as marriage, health and having children in the household and the nature of the working environment statistically make a greater contribution to happiness than income.While happiness can be a genetic aspect of ones personality, some people could become even happier if they were educated, had a healthy lifestyle, positive working relationships in the company of happy people and good friendships, and could contract affordable debt, enabling them to buy the right things.

Material aspirations change with gains in income.Some people seek happiness through gratification of the senses and material possessions.For them, the quest for more never ends, but leads them to the treadmill of unhappiness.However, one cannot expect to experience permanent happiness from impermanent worldly objects.Accordingly, some people seek spiritual rather than material happiness.This may be a matter of individual taste and preference.But good taste is what increases happiness, and vice versa (Layard, 2006:C30).Life satisfaction involves more than just income.Happiness can be bought in other 'currencies', like religion, education, friendships and family relationships.

Table 1
1
Total variance explained

Table 1 : Component Initial Eigenvalues Extraction sums of squared loadings Rotation sums of squared loadings Total % of Variance
1Cumulative %Total% of varianceCumulative %Total% of varianceCumulative %12.02214.44414.4442.02214.44414.4441.77112.65312.65321.80512.89127.3351.80512.89127.3351.70112.15124.80431.43710.26237.5971.43710.26237.5971.40110.00634.80941.3389.55847.1551.3389.55847.1551.3779.83544.64551.2328.80255.9571.2328.80255.9571.2448.88453.52961.0547.52863.4851.0547.52863.4851.2368.82762.35671.0147.24670.7311.0147.24670.7311.1728.37470.7318.7895.63476.3659.7395.28281.64610.6734.80786.45411.5874.19190.64412.5073.62494.26813.4213.00597.27314.3822.727100.000Extraction method: principal component analysis.

Table 2
2

Component1234567Marital status.828-.053-.026.051-.067-.152-.033Number of children.822.010.041-.043.079.182.048Health-.245.809.079.057-.045-.029.089Job/Working environment.106.731-.096.083-.073.191-.218Religion.205.570-.041.298.114-.227.394Income received.351-.052.782-.089-.106-.027-.078Level of education-.369.027.764-.076.090.018-.067Debt level.027-.001-.043.792.075.060-.151Friendships-.035.304-.092.655-.168-.012.056Debt feel.002.057-.064-.188.866-.060-.168Age-.003-.276.081.325.631.125.319Types debt.136-.022.220.172-.058.788.062Ethnic group-.133.092-.325-.125.078.667-.120Gender-.009-.008-.102-.131-.048-.015.880Extraction method: principal component analysis.Rotation method: varimax with Kaiser normalization.(a) Rotation converged in 8 iterations.
AcknowledgementsThe author would like to express his thanks to Professor S. Koch, Dr R. Simson, K. Ingleton, and the reviewers of this paper for their helpful comments and assistance.
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The genomics and proteomics of biofilm formation
2003

Karin Sauer email@example.com
Address: State
University of New York at Binghamton
104 Science III

Vestal Parkway East
13902BinghamtonNYUSA

The genomics and proteomics of biofilm formation

Genome Biology
42192003Genome Biology 2003, 4:219Minireview
comment reviews reports deposited research interactions information refereed researchAbstractBacterial communities that are attached to a surface, so-called biofilms, and their inherent resistance to antimicrobial agents are a cause of many persistent and chronic bacterial infections. Recent genomic and proteomic studies have identified many of the genes and gene products differentially expressed during biofilm formation, revealing the complexity of this developmental process.The electronic version of this article is the complete one and can be found online at

In nature, the majority of bacteria live in close association with surfaces, as complex communities referred to as biofilms [1,2]. Biofilms (so called because macroscopically they do look like a thin layer of slime) have a distinct architecture, consisting of tower-and mushroom-shaped microcolonies encased in a hydrated matrix of exopolymeric substances, polysaccharides and proteins that are produced by the resident microorganisms. Compared with their planktonic (non-adherent) counterparts, the compact microbial consortia present in biofilms show extraordinary resistance to conventional biocides, antimicrobial treatments and the immune defense responses of the host. Formation of these sessile communities and their inherent resistance to antimicrobial agents are at the root of many persistent and chronic bacterial infections. Biofilms have been shown to colonize a wide variety of medical devices and to be associated with several human diseases, such as native valve endocarditis, burn wound infections, chronic otitis media with effusion and cystic fibrosis. Recent advances in our understanding of the genetic and molecular basis of bacterial community behavior point to therapeutic targets that may provide a means for the control of biofilm infections.

Rethinking biofilms

Looking back, research on biofilms has come a long way since the initial characterization of a biofilm by Antoni van Leeuwenhoek. The first descriptions of specific genes that are up-or down-regulated in biofilm bacteria were made using transcriptional lacZ reporter-gene fusions [3,4] and led to the belief that bacterial attachment initiates the expression of a set of genes that culminates in a biofilm phenotype ( Figure 1) [2]. That significant fractions of the bacterial genome could be involved in, or affected during, biofilm formation was shown in Escherichia coli in a genome-wide screen using random chromosomal insertions of a lacZ reporter gene fusion construct [5]. Prigent-Combaret et al. [5] showed that bacteria within biofilms encounter higherosmolarity conditions, greater oxygen limitation, and higher cell density than in the liquid phase. With so many genes involved, it is perhaps not surprising that biofilm formation is regarded as a developmental process (Figure 1), not unlike that observed in the formation of fruiting bodies containing spores by the soil bacterium Myxococcus xanthus and sporulation in Bacillus subtilis [6].

The availability of complete bacterial genome sequences, together with the development of microarrays with which the expression of the entire genome of an organism grown under two conditions can be assayed, has launched the postgenomic era of biofilm research and generated a wealth of new information. But a comparison of the differentially expressed gene sets identified in several recent DNA microarray studies [7][8][9][10] reveals that no common expression pattern for biofilms has yet emerged. Instead, in different studies different genes are found up-and down-regulated, in varying numbers ranging from 1% to 38% of the total genome. One explanation for these apparent discrepancies is that DNA microarrays provide a sensitive but transient snapshot of gene expression and that gene expression does not necessarily directly correlate with phenotype. This article will focus on the discrepancies that may arise from differences in experimental scenarios and between the species used; for example, Gram-negative bacteria differ from Gram-positive bacteria with respect to cellwall composition, the molecules involved in quorum sensing (the ability of bacteria to communicate with each other in a population to coordinate population behavior in response to environmental cues), and some transcriptional regulators.

Biofilm formation in Gram-negative bacteria

Using DNA microarrays, gene expression in E. coli biofilms (grown in a silicone flow chamber for a total of 40 hours at varying flow rates) was compared with expression in planktonic cells in stationary phase [7]. The comparison revealed an overall change of more than 600 genes, with 9% of the whole genome being activated and 4.5% repressed in the biofilm cells. When the transcriptional profile of biofilm cells was compared with that of exponentially grown cells, a different expression pattern emerged: only 230 genes were found to be differentially expressed, with 4.8% up-and 0.5% down-regulated in biofilm cells [7]. Overall, the expression of only 79 genes, representing 1.84% of the E. coli genome, was significantly altered during biofilm growth compared with planktonic growth. Among the genes that showed increased expression in biofilms were three involved in adhesion and autoaggregation, several encoding structural proteins such as OmpC, OmpF and OmpT, lpxC (encoding a protein associated with lipid A biosynthesis), and slp (encoding an outer-membrane lipoprotein induced after carbon starvation). Some of these genes (slp and ompC) have recently been associated with the initial steps of E. coli biofilm formation on abiotic surfaces [5,11].

The microarray analysis of biofilms by Schembri et al. [7] also revealed differential expression of genes under oxygenand nutrient-limiting conditions, and of genes associated with enhanced heavy-metal resistance. Interestingly, although quorum sensing has been shown to be important in biofilm formation in other species, such as Pseudomonas aeruginosa [12], no genes regulated in response to quorum sensing were found in the study of biofilm formation by Schembri et al. [7]. Furthermore, their E. coli transcriptome analysis did not reveal changes in the expression of components of the Cpx two-component signal transduction  system, which senses changes in the environment and responds to general stress conditions in the extracytoplasmic compartment by activating genes that encode periplasmic protein-folding and protein-degradation factors. The Cpx transduction system in E. coli has previously been demonstrated to be involved in surface sensing and adhesion [13] and in the modulation of the expression of curli, thin bacterial appendices that are involved in adhesion and biofilm formation [14], so failure to find its genes regulated during biofilm formation is surprising.

A DNA microarray analysis of Pseudomonas aeruginosa detected only 1% of genes as differentially expressed in the biofilm growth mode, with 0.5% of the genes being activated and about 0.5% being repressed [8]. Whiteley et al. [8] assigned the differentially regulated genes to motility, attachment, translation, metabolism, transport and regulatory functions, and found that temperate phage genes were the most highly activated. This initial microarray analysis of P. aeruginosa biofilms [8] showed that, on average, gene expression in biofilm cells was remarkably similar to gene expression in planktonic cells maintained under similar environmental conditions, namely dense communities with high cell densities (10 10 cells per milliliter). These conditions activate the bacterial communication system that would be expected to trigger quorum sensing and regulate between 353 [15] and 616 genes [16], but no quorum-sensing-regulated genes were identified in this study [8]. The latter is an unexpected result because the process of biofilm development has previously been shown in P. aeruginosa to involve quorum sensing [12]. Furthermore, bacterial communication via quorum sensing has been reported to be important in the production of virulence factors and antibiotic resistance. It has therefore been suggested that quorum sensing may contribute to the ability of P. aeruginosa to initiate infection and to persist in a host as a biofilm. Data from many models of both acute infection and chronic infection have supported the hypothesis that quorum sensing is important in P. aeruginosa pathogenesis and biofilm formation [16].

One protein known to play a key role in biofilm formation is RpoS, the S subunit of RNA polymerase [17]. It governs the expression of many genes induced during the stationary phase of growth and is considered to be the master regulator of the general stress response in E. coli [18]. Schembri et al. [7] noted that 46% of the genes that were found to be differentially expressed during biofilm growth were under the control of RpoS, and deletion of rpoS rendered E. coli incapable of establishing sessile communities [7]. In P. aeruginosa, the role of a homolog of E. coli RpoS seems to be the opposite of the role of RpoS in E. coli: the P. aeruginosa rpoS gene was found to be repressed in biofilms, and rpoS-deficient mutants not only formed better biofilms than wild-type cells but were more resistant to antimicrobial treatment [8]. This finding is consistent with earlier reports that P. aeruginosa rpoS mutants were hypervirulent in a mouse model [19].

Biofilm formation in Gram-positive bacteria

To analyze global gene expression in B. subtilis using microarrays, biofilms were grown under stagnant growth conditions in a beaker, and after 8, 12, and 24 h the total content of the growth vessel, which contained both biofilm and planktonic cells, was harvested for RNA isolation [9]. For comparison, the RNA of a purer population of planktonic cells was isolated from cells grown with shaking to late exponential phase. A total of 519 genes were identified as differentially expressed during the time-course of biofilm formation. More than 55% of these were expressed at only one of the three time points, indicating temporal control of gene expression during biofilm formation. Most of the differentially expressed genes were involved in phage-related functions, membrane bioenergetics, glycolysis, and the tricarboxylic acid cycle, and in addition there were many genes involved in motility and chemotaxis.

Although the role of motility in biofilm formation has been shown in other experimental models, such as E. coli and P. aeruginosa biofilms [5,20], it is noteworthy that motility and chemotaxis seem to be associated with only the very initial steps of biofilm formation, namely the transition to the sessile mode of growth ( Figure 1). It should be noted that batch cultures grown in beakers and microtiter plates are models in which it is difficult to produce steps past the initiation of biofilm formation, so the findings should be considered as somewhat limited as fully mature biofilms cannot be studied under these experimental conditions [21].

Stanley et al. [9] used expression profiling to identify transcriptional regulators that were affected during biofilm formation in B. subtilis, by extrapolating from the expressed genes expressed to their regulators. Using this indirect approach, several transcription factors were identified, including Spo0A and the starvation-activated transcription factor H . Spo0A was previously shown to be required for biofilm formation [22] and for directing the development of endospores. Furthermore, 40 genes responsive to glucose concentration were found in the study by Stanley et al. [9], who concluded that glucose inhibits biofilm formation through the catabolite control protein CcpA. A role for glucose in biofilm formation has also been proposed for Streptococcus mutans [10] and E. coli [23] when grown under stagnant batch growth conditions. In the case of E. coli, the availability of glucose affected biofilm formation through the carbon storage regulator CsrA; disruption of csrA significantly decreased biofilm formation [23].

Alternative approaches to studying biofilms

In addition to microarray analyses, in vivo expression technology has recently been used to study global gene expression in P. aeruginosa biofilms [24]. This technology was originally developed to study virulence genes that are repressed during growth on laboratory media but expressed in pathogenic bacteria during an infectious process in a host. Finelli et al. [24] have used gene-fusion constructs that complement an attenuating adenine auxotrophic mutation to identify promoters that are turned on in vivo in P. aeruginosa biofilms. P. aeruginosa derivatives under flowing conditions were allowed to establish biofilms on the interior surface of silicone tubing, and after five days the biofilm was harvested and cells plated on adenine-containing medium to isolate single positive clones for further analysis.

Using in vivo expression technology, only five genes essential for P. aeruginosa biofilms were identified and subsequently confirmed by insertional mutation [24]. Mutation in PA5065, a homolog of E. coli ubiB (involved in ubiquinone biosynthesis), was lethal, and mutation in PA2247 (encoding 2-oxoisovalerate dehydrogenase) has not been characterized in detail [24]. Mutations in three other genes, PA0240 (encoding a putative porin), PA3710 (encoding aliphatic alcohol dehydrogenase), and PA3782 (encoding an AraC-like transcriptional regulator), had no effect on planktonic growth but caused defects in biofilm formation in static and flowing systems. Interestingly, in competition experiments, these three P. aeruginosa mutants had reduced fitness compared with the parent strain: they comprised less than 0.0001% of total biofilm cells after five days growth in culture, indicating a role for the mutated genes in the establishment of sessile communities. Finelli et al. [24] concluded that they had identified novel genes that did not affect planktonic growth but were important for biofilm formation, development, and fitness. None of the genes identified in this study was detected in previous DNA microarray analyses of E. coli [7] or P. aeruginosa [8].

Proteomics refers to the comparative identification of all proteins expressed under various conditions, as found for example, by two-dimensional gel electrophoresis. Although low resolution and detection limits are common pitfalls, this technique is an essential complement to transcriptome analysis because it allows the detection of proteins, the functional entities of a cell, and of post-translational protein modifications, which cannot be predicted by mRNA expression analysis. Unfortunately, to date only limited information about biofilm proteomics is available, making a thorough comparison between transcriptomes and proteomes difficult. My colleagues and I [25] showed by twodimensional gel electrophoresis combined with reporter-gene analysis and microscopy that biofilm communities of P. aeruginosa displayed at least five distinct physiologies during biofilm development (Figure 1) [25]. The five stages were visible when biofilms were grown on the interior surface of silicone tubing under flowing conditions over a 12day period.

A large number of proteins were found to be differentially produced during the different stages of biofilm development; several proteins were differentially expressed after one day of biofilm growth and the protein-expression pattern showed maximum change compared with the expression pattern in planktonic cells in mature biofilm cells [25]. At each of the five stages, the majority of differently produced protein spots on gels were found to be overexpressed; 23 of the overproduced proteins were involved in oxidative damage, production of exopolymeric substances, aerobic and anaerobic metabolism, and membrane transport. After maturation, biofilm dispersion and reversion to the planktonic mode of growth occurred ( Figure 1) and most of the differentially produced proteins were repressed. Similar observations were made for Bacillus cereus, in which distinct and reproducible protein patterns were observed between biofilms of different ages [26].

In conclusion, although it is apparent that biofilms have gene-expression patterns that differ from those of planktonic bacteria, it is also clear that we still have to decipher the genetic basis of biofilm formation. Much more work is also still needed if we are to completely describe the physiological changes that occur during biofilm formation. The detection of stage-specific physiologies and the display of multiple phenotypes during biofilm development may hold clues to the differences among the various DNA microarray analyses described so far.

Figure 1
1A model of the stages of bacterial biofilm development. At stage 1, the bacterial cells attach reversibly to the surface. Then, at stage 2, the cells attach irreversibly, a step mediated mainly by exopolymeric substances, and the cells lose their flagella-driven motility. At the next stage (3), the first maturation phase is reached, as indicated by early development of biofilm architecture. The second maturation phase is reached at stage 4 with fully mature biofilms, as indicated by the complex biofilm architecture. At the dispersion stage (5), single motile cells (dark cells on the figure) disperse from the microcolonies. Adapted from[27].
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