Ribosome surface properties may impose limits on the nature of the cytoplasmic proteome
Many processes in biological cells depend on interactions between macromolecules ( proteins and nucleic acids ) and thus on the ability of these macromolecules to find each other by translational diffusion . This is especially important in prokaryotes because of the virtual absence of active mechanisms of cytoplasmic transport . It is clear that macromolecules need to diffuse for cells to function . To what extent the actual rate of this diffusion matters depends on the process under consideration and is in many cases unknown . For Brownian diffusion the rate of movement is characterized entirely by the diffusion coefficient , D . The exact value of the diffusion coefficient is important to the rate of a process only if it is diffusion limited , e . g . if the necessary conformational changes in an enzyme are faster than the diffusion of reactants . Arbitrarily lowering a diffusion coefficient , e . g . by osmotic stress , can make a process diffusion limited . Examples of diffusion-limited processes are binding of tRNA complexes to the ribosome , which leads to limitation in cell growth ( Klumpp et al . , 2013 ) ; and the binding of barstar to barnase , which we know to be diffusion limited because the proteins are designed to have an increased association rate by electrostatic interactions ( Vijayakumar et al . , 1998 ) . Because protein diffusion is influenced by the environment , we need to determine diffusion coefficients in the context of the cell . The cytoplasm of cells is not only crowded with macromolecules ( van den Berg et al . , 2017 ) but also consists of various types of nucleic acids and >1000 types of protein ( see proteome analysis below ) ; though only 50 protein types make up 85% of the cytoplasmic proteome of E . coli ( McGuffee et al . , 2010 ) . Various studies report on the presence of weak and nonspecific interactions between these components . NMR studies on proteins , either in the E . coli cytoplasm ( Crowley et al . , 2011; Ye et al . , 2013 ) or cell lysates ( Latham and Kay , 2013 ) , reveal that there are weak interactions between E . coli proteins and proteins cytochrome c , ubiquitin , and calmodulin . In a computational study on protein interactions it was found that in E . coli more highly expressed proteins are constrained in evolution to be less sticky ( Levy et al . , 2012 ) , suggesting that nonspecific interactions are common and consequential . The transient macromolecular interactions in vivo , resulting from molecular evolution , are referred to as the quinary structure of proteins ( McConkey , 1982 ) , and we discriminate these from the more generic nonspecific interactions that occur between molecules without coevolved interfaces . In this study we set out to study the diffusion coefficients of proteins as a function of their surface properties and thus probe the boundary conditions for the generic nonspecific interactions . Our interest in this was piqued by four datasets from the literature . The first is the scattering of diffusion coefficients in the E . coli cytoplasm around a common downward trend when they are plotted against protein molecular weight; the dataset suggests that not only size ( and shape ) matter ( Mika and Poolman , 2011 ) . Second , the diffusion coefficient of GFP is faster in the cytoplasm of osmotically-adapted E . coli cells than in osmotically-upshifted cells , even at similar cytoplasmic macromolecule volume fraction ( Konopka et al . , 2009 ) . Third , the diffusion coefficient of GFP drops much faster with cell volume ( after an osmotic upshift ) in Lactococcus lactis than in E . coli ( Mika et al . , 2014 ) . Fourth , the slowing of diffusion in metabolic energy-depleted cells suggests changes in the dynamic structure of the cytoplasm ( Parry et al . , 2014; Joyner et al . , 2016; Munder et al . , 2016 ) . In all four cases differential interactions of proteins with their surroundings may play a role , which are grounded in the surface properties of the macromolecules . Besides ( possibly ) giving insight into these four phenomena , studying the dependence of mobility on protein surface properties adds to our general quantitative understanding of diffusion; complementing studies on the relation between diffusion coefficients and protein size ( Mika and Poolman , 2011; Mika et al . , 2014; Kumar et al . , 2010; Nenninger et al . , 2010; Mika et al . , 2010 ) , diffusion coefficients and macromolecular crowding ( Konopka et al . , 2009; Mika et al . , 2014; Mika et al . , 2010; Konopka et al . , 2006; van den Bogaart et al . , 2007 ) , and the dynamic structure of the cytoplasm ( Spitzer and Poolman , 2009; Spitzer and Poolman , 2013 ) . Here , we use a set of GFP variants with a net charge that ranges from −30 to +25; we also studied two variants of +11 GFP that differ in the distribution of the charge over the surface . All diffusion coefficients were determined by fluorescence recovery after photo-bleaching ( FRAP ) . We study these proteins in the bacteria Escherichia coli and Lactococcus lactis and the archaeon Haloferax volcanii . These three organisms differ in their cytoplasmic ionic strength as shown by measurements on the dominant cation , K+: E . coli ( 0 . 2 M ) ( Shabala et al . , 2009 ) , L . lactis ( 0 . 8 M ) ( Poolman et al . , 1987 ) ( note: L . lactis used to be called Streptococcus cremoris ) , and Hfx . volcanii ( 2 . 1 M ) ( Pérez-Fillol and Rodríguez-Valera , 1986 ) ; these values are dependent on environmental conditions , but the differences in potassium ion concentration likely report the differences in ionic strength in these prokaryotes . The difference in ionic strength between E . coli and L . lactis is also reflected in the higher turgor pressure of L . lactis ( Mika et al . , 2014 ) .
We performed fluorescence recovery after photo-bleaching ( FRAP; see Figure 1a , b ) to determine the diffusion coefficients of surface-modified variants of GFP in the E . coli cytoplasm . We determined the diffusion coefficient of the −30 , –7 , 0 , +7 , +11b , +15 and +25 variants of GFP; see Figure 1c for structural models . The numbers indicate the net charge; the ‘b’ in +11b GFP refers to the distribution of the charge over the surface and will be discussed in more detail below . For each variant we measured the diffusion coefficients on cells from at least three independent cultures , and for each cell we obtained a single diffusion coefficient . For each GFP variant we plotted the histogram of diffusion coefficients over the population of cells ( Figure 1d ) . The −30 , –7 and 0 variants of GFP all have the same mean diffusion coefficient of 10–11 µm2/s ( for table of mean diffusion coefficients see Supplementary file 1B ) . At +7 GFP the diffusion coefficients start to drop , down to a mean value of 0 . 14 µm2/s for +25 GFP . For the +15 and+25 GFP variants we observed heterogeneous fluorescence in some cells . This ranged from a somewhat higher fluorescence at the poles to a clear ring around the outskirts of the cells ( Figure 2—figure supplement 1a ) . For +15 GFP we were able to get rid of the heterogeneities by inducing for a shorter period of time . For +25 GFP , we excluded cells with extreme heterogeneities ( see Figure 2—figure supplement 1a ) . The cells with only slightly inhomogeneous fluorescence had similar diffusion coefficients to cells with homogeneous fluorescence and were included in the data ( Figure 2—figure supplement 1b ) . The heterogeneities are probably due to exclusion of large complexes ( +25 GFP forming clusters of ribosomes ) from the nucleoid ( see below ) . Why does the diffusion coefficient drop with net positive charge ? The first thing to realize is that almost nothing in the cytoplasm of the E . coli cell truly stands still . The membrane rearranges itself continuously and the DNA has some diffusive motion and rearranges itself during the cell cycle . If +25 GFP would stick to another average sized protein it would not move more slowly than the combination of the two can diffuse . If +25 GFP were to bind some bigger complex , like β-galactosidase ( ~500 kDa ) with a diffusion coefficient of ~1 µm2/s , it would diffuse with a similar rate as β-galactosidase . Based on a census of elements present in E . coli cells this means that for +25 GFP to diffuse with a diffusion coefficient as low as 0 . 14 µm2/s it needs to bind to membrane proteins , DNA and/or ribosome-mRNA complexes . For membrane proteins with 12–14 transmembrane helices in E . coli and L . lactis , D is 0 . 02–0 . 03 µm2/s ( Mika et al . , 2014; Kumar et al . , 2010 ) . Describing the motion of DNA with a diffusion coefficient is somewhat of a stretch , as its parts do not move freely , but apparent values of 0 . 000035–0 . 00007 µm2/s have been reported ( Reyes-Lamothe et al . , 2008 ) . In fast growing cells , we expect ribosomes and mRNA to be associated most of the time ( Sanamrad et al . , 2014 ) , and D is 0 . 04 µm2/s when a one-component model is used for fitting the data ( Bakshi et al . , 2012 ) . In another study free and bound ribosomes were discriminated and D values of 0 . 40 ( ~15% ) and 0 . 055 µm2/s ( ~85% ) were found ( Sanamrad et al . , 2014 ) . So membrane proteins , DNA and ribosomes-mRNA all have diffusion coefficients low enough to cause the drop in mobility of +25 GFP . Fluorescence images show that most , if not all , fluorescence is located in the cytoplasm , leaving DNA and/or ribosome-mRNA as the most likely ( major ) binding partners . We cannot rule out that some of the GFP binds to the membrane but we did not find evidence for it in our images of E . coli cells . We also determined diffusion coefficients of the GFP variants in L . lactis and Hfx . volcanii ( Figure 2 and Supplementary file 1B ) . For L . lactis the mean diffusion coefficient of −7 GFP ( 6 . 2 µm2/s ) is lower than for E . coli ( 10 µm2/s ) . However , D drops less with positive net charge so that for +25 GFP the mean diffusion coefficient is higher in L . lactis ( 0 . 61 µm2/s ) than in E . coli ( 0 . 14 µm2/s ) . This can be explained by the higher cytoplasmic ionic strength of L . lactis , reducing the affinity of positive GFPs to hypothetical negatively-charged binding partners . For Hfx . volcanii the drop in diffusion coefficient is even less steep , with the mean diffusion coefficient dropping from 5 . 5 µm2/s , for −7 GFP , to 1 . 9 µm2/s , for +25 GFP . The shallower drop in diffusion coefficient with net positive charge as compared to both L . lactis and E . coli can again be explained by a difference in ionic strength . Another possible contribution to the high +25 GFP diffusion coefficient in Hfx . volcanii is the presence of more negative proteins than in E . coli and L . lactis , which may titrate GFP away from its slower binding partner ( see proteome analysis below ) . We also note that in Hfx . volcanii the diffusion coefficient of −30 GFP is higher than of −7 GFP , 10 µm2/s compared to 5 . 5 µm2/s , which may be caused by a less negative binding partner for GFP in Hfx . volcanii than in E . coli . Next , we determined the diffusion coefficient of −30 , –7 , +15 and +25 GFP in E . coli after resuspending the cells in medium with a higher osmolality . It is known that the GFP diffusion coefficient drops drastically after an osmotic upshift ( Konopka et al . , 2009; Mika et al . , 2014; Mika et al . , 2010 ) . We now observe what happens after combining two causes for slowed diffusion: osmotic upshift ( increased crowding ) and protein surface charge . The cells were grown at an osmolality of 0 . 28 Osm and resuspended in media of 0 . 55 or 1 . 2 Osm ( adjusted with NaCl ) . In 0 . 55 Osm medium the diffusion coefficients did not change much ( Figure 3a and Supplementary file 1B ) , similar to what was observed before for wildtype GFP ( Konopka et al . , 2009 ) . In 1 . 2 Osm medium the diffusion coefficients of all variants dropped ( Figure 3a and Supplementary file 1B ) . The degree of the drop is 56- , 28- , 16- , and 7-fold ( between medians ) for −30 , –7 , +15 and +25 , respectively , and this difference may be a consequence of the increased cytoplasmic ion concentration that accompanies the osmotic upshift . Thus , the fold-change is less for the positive proteins because the electrostatic screening may compensate partly for the increased crowding effect . For −30 , –7 , 0 , +7 , +11b , +15 and +25 GFP , the charge is distributed more or less equally over the surface of the protein . We also determined how a more localized charge affects the diffusion . The +11a variant of GFP has the positive charge unequally distributed , compared to +11b GFP ( Figure 3d ) . We determined diffusion coefficients for the +11a and +11b variants by FRAP . Histograms of the diffusion coefficients over populations of cells are shown in Figure 3c . The mean diffusion coefficient of +11b GFP is 2 . 7 µm2/s and that of +11a GFP is 0 . 76 µm2/s ( Supplementary file 1B ) . So , it clearly matters how the net charge is distributed over the GFP surface . For +11a GFP we also see heterogeneous distributions , similar to +15 and +25 GFP , which could be prevented by inducing for a shorter amount of time . To find out whether the positive GFP variants are bound to DNA or ribosomes-mRNA or both , we first determined the co-localization between GFP and DNA . We expressed +25 GFP in E . coli , labelled the nucleoid with DRAQ-5 and shrunk the nucleoid with chloramphenicol . We compared the fluorescence profile , along the length of the cells , of +25 GFP with that of DRAQ-5 ( Figure 4a and Figure 4—figure supplement 1 ) . In all cells the distribution of +25 GFP matched the dimensions of the cells . In nine cells ( Figure 4—figure supplement 1a–i ) out of 46 the nucleoid had shrunk and in all these cells + 25 GFP did not co-localize with DNA . In some cells + 25 GFP was occluded from the DNA , which has been seen before for ribosomes ( Bakshi et al . , 2012 ) . In the other cells the nucleoid did not shrink and the DNA and +25 GFP overlapped ( see Figure 4—figure supplement 1j–p ) . We conclude that DNA is not the major binding partner for +25 GFP . Next , we determined if DNA affects the mobility of +25 GFP by analyzing the diffusion of −7 and +25 GFP in DNA-free regions of E . coli cells . We created DNA free regions large enough for FRAP measurements by first treating cells with cephalexin , to elongate the cells , and then with chloramphenicol , to shrink the nucleoid . We visualize the position of DNA by adding DRAQ-5 . Only a fraction of the cells had enough GFP fluorescence for FRAP and sufficient DRAQ-5 fluorescence for visualizing the position of DNA , and these were analyzed ( Figure 4—figure supplement 2a and b ) . We find that for both −7 and +25 GFP the diffusion coefficient has dropped after treatment of the cells with cephalexin and chloramphenicol ( Figure 4—figure supplement 2c and d ) . There is a big difference between the mean diffusion coefficient of −7 and +25 GFP after treatment and in the absence of DNA ( 35-fold ) . A similar difference between −7 and +25 GFP was found in cells that were not treated and in the presence of DNA ( 85-fold ) . This shows that the drop in +25 GFP diffusion rate is not dependent on DNA . Both −7 and +25 GFP are somewhat excluded from DNA ( nucleoid ) but the effect is largest for +25 GFP; this is another piece of evidence suggesting that +25 GFP binds to ribosome-mRNA and not to DNA . It has been shown that the 30S ribosomal subunit in E . coli increases its diffusion coefficient , from 0 . 04 µm2/s to 0 . 6 µm2/s , after treatment with rifampicin ( Bakshi et al . , 2012 ) . Rifampicin stops transcription and after adding it to E . coli cells the pool of mRNA plummets , with 90% of the mRNAs having a half time of less than 8 min ( Bernstein et al . , 2002 ) . We determined the diffusion coefficient of +25 GFP in E . coli as a function of time after the addition of rifampicin and compared this to the situation without rifampicin ( Figure 4b ) . We found that after treatment with rifampicin , the diffusion coefficient of +25 GFP increases for 20 min and then levels off . This coincides with the time needed to degrade most of the mRNA . Importantly , the diffusion coefficient after 20 min of rifampicin treatment is close to the value of the 30S and presumably the 50S subunit . We also find that the fluorescence of +25 GFP expressing cells becomes more homogenous after rifampicin treatment . Together , these findings indicate that the positive GFP variants bind to ribosomes , and that this is the major cause for their slow diffusion . We can’t rule out that some +25 GFP binds to mRNA , but it is not a major contributor to the decrease of +25 GFP diffusion coefficient . With reasonable confidence we also put aside two other hypotheses: ( i ) differential partitioning of negative and positive GFPs in different cytoplasmic phases; and ( ii ) formation of big clusters of positive GFPs with negative proteins . Finally , we find that the variation in diffusion coefficient between cells is smaller in the presence than in the absence of rifampicin , suggesting that part of the spread in the diffusion relates to ongoing transcription . To substantiate our in vivo findings on the binding of positive GFPs to ribosomes , we determined whether −7 and +25 GFP co-localize with ribosomes and/or DNA on a sucrose gradient . For this experiment we used ( ribosome containing ) lysates of −7 or +25 GFP expressing E . coli cells . The cell lysates were 200–300 times diluted relative to the cytoplasmic contents . The contents of the lysates were separated by centrifugation on a linear sucrose gradient and we determined the presence of the GFPs , by fluorescence spectroscopy , in fractions taken along the length of the gradient . We also determined the presence of ribosomes by electron microscopy . We observed a clear difference in the position of −7 and +25 GFP along the gradient , with the peak of the +25 GFP distribution coinciding with the presence of ribosomes ( Figure 5a and c ) . We do not know the exact DNA content of the lysates , so we performed two more experiments in which we added pure DNA to the +25 GFP cell lysates before separating their contents on sucrose gradients . We used a DNA/ribosome ratio that is comparable ( 0 . 02 g/L DNA , experiment 1 ) , or five times higher to that in the cell ( 0 . 12 g/L DNA , experiment 2 ) ( Milo and Phillips , 2015 ) . The position of DNA along the gradient was determined in a separate experiment in which only the pure DNA was added to a sucrose gradient . Even at the highest concentration of DNA , +25 GFP co-localizes with ribosomes and not with DNA ( Figure 5b ) . From the combination of sucrose gradient experiments and our in vivo studies described above , we conclude that +25 GFP binds predominantly to ribosomes . We also determined if purified ribosomes are able to bind purified +25 or −7 GFP by analyzing solutions of ribosomes mixed with GFPs with size-exclusion chromatography ( SEC ) . At physiological salt concentrations ( Shabala et al . , 2009 ) we observe that upon mixing ribosomes and +25 GFP , aggregates are formed ( Figure 5e ) . These aggregates are not seen when −7 GFP is mixed with ribosomes . In the SEC experiment , the association of ribosomes and +25 GFP results in a decrease of the 280 nm absorbance peak at around 10 mL , because the aggregates are removed by centrifugation ( Figure 5d ) . This effect scales with increasing +25 GFP concentration . In line with these observations on binding of +25 GFP to ribosomes , we observe an increase in the fluorescence at the ribosome elution volume when we mix ribosomes and +25 GFP ( Figure 5f ) . The control experiment with −7 GFP shows that the anionic protein does not bind to ribosomes and elutes on SEC at around 17 . 5 ml ( Figure 5g ) . From these results we conclude that +25 GFP indeed associates with ribosomes in vitro .
The diffusion coefficient of GFP in cells is a function of free and bound GFP . If the exchange between these two states is longer than the time of the FRAP measurement one will observe two populations . If the two states exchange on a timescale much shorter than the time of the FRAP measurement the diffusion can be described by a single diffusion coefficient ( Deff ) : ( 1 ) Deff= ffree Dfree+ ( 1−ffree ) Dbound We used Equation ( 1 ) to calculate the fraction of free GFP for each of the GFP variants in E . coli , L . lactis and Hfx . volcanii ( see Materials and methods for derivation of Equation ( 1 ) ) . We made a number of assumptions: ( 1 ) the exchange between free and bound state is much faster than the FRAP measurement; ( Vijayakumar et al . , 1998 ) the highest diffusion coefficient of all variants in a given organism reflects the free state of GFP; ( 3 ) GFPs bind solely to ribosomes; ( 4 ) the total number of binding sites on all ribosomes is higher than the number of GFPs; ( Crowley et al . , 2011 ) the decrease of diffusion coefficient with net positive charge has the same origin in all three organisms; and , finally ( 6 ) the ribosome diffusion coefficient is the same in all three organisms . Justifications for these assumptions are described in the Materials and methods section . The results are shown in Figure 6—figure supplement 1 . From the analysis we conclude that even in Hfx . volcanii , with its high internal ion concentration , a major fraction ( 0 . 81 ) of +25 GFP is still bound to ribosomes . Next , we estimated the dissociation constant ( Kd ) of the association between GFP and ribosomes . For E . coli , under our growth conditions , the number of ribosomes per µm3 is about 17000 ( Vendeville et al . , 2011 ) , which corresponds to a concentration of 10 µM . GFP probably binds to the RNA that is exposed on the surface of the ribosome and probably does so nonspecifically . The ribosome has a diameter of 20 nm , which yields a surface area of 1260 nm2 , assuming a spherical shape . About half of this surface area is RNA so we end up with 630 nm2 . The diameter of GFP is 3 . 5 nm , giving a 9 . 6 nm2 cross section . Dividing the ribosome RNA surface area by the GFP cross section gives a maximal number of binding sites of 66 . This means that the concentration of binding sites is 660 µM . To calculate Kd we use: ( 2 ) fbound=[binding site]Kd+[binding site] This equation is valid when the number of binding sites is significantly higher than the number of GFPs . Using a fraction of bound +25 GFP of 0 . 99 in E . coli , we obtain Kd = 6 . 7 µM . If we make the assumption that the concentration of ribosomes in L . lactis and Hfx . volcanii is the same as in E . coli , then the Kd for binding of +25 GFP to a ribosome binding site is 65 µM for L . lactis and 155 µM for Hfx . volcanii . In this section we seek to explain: ( i ) the relation between Deff and cytoplasmic ionic strength; and ( ii ) the relation between Deff and net charge of GFP . To explain ( i ) we first compare our values to literature data on electrostatic interactions between proteins in dilute solution . To make the comparison possible we relate Kd , rather than Deff , to ionic strength . In Figure 6a we plot the Kd versus ionic strength of the interaction between barnase and barstar ( Schreiber and Fersht , 1993 ) , colicinE9 and Im9 ( Wallis et al . , 1995 ) , and different forms of thrombin and hirudin ( Stone et al . , 1989 ) . The ionic strength dependence of the interaction of +25 GFP with ribosomes ( recorded in E . coli , L . lactis and Hfx . volcanii; Figure 6b ) is similar to that of the three protein pairs in dilute solutions ( Figure 6a ) ; the Kd increases with ionic strength and levels off at higher ionic strength . To get more insight into the interaction we applied a semi-empirical equation that was successfully used to describe the ( partly ) electrostatic interaction between the proteins thrombin and hirudin ( Stone et al . , 1989 ) : ( 3 ) ΔGb∘=ΔGnio∘+ΔGio0∘e−C1I1+C1I This equation was derived from Debye-Hückel theory and was subsequently modified to account for behavior at higher ionic strength . Here ΔGb∘is the total binding energy , ΔGnio∘ is the binding energy due to non-ionic interactions , ΔGio0∘ is the binding energy due to electrostatic interactions in the absence of ions , C1 is a parameter that depends on the distance between charges and the screening effects that are not due to ions , and I is the ionic strength . To apply Equation 3 we need to relate the KD and ΔGb∘: ( 4 ) KD=eΔGb∘RT We fitted the +25 GFP interaction data with a combination of Equations ( 3 ) and ( 4 ) and obtained the following parameter values: ΔGnio∘= −20 400 J mol−1 , ΔGio0 ∘= −28 900 J mol−1 , and C1 = 1 . 53 . We had expected that the non-ionic interaction free energy would be close to zero , but if we impose this conditions the fit becomes bad ( Figure 6c ) . The bending off at higher ionic strengths depends on ΔGio0∘ being negative; we expect ΔGio0∘ to be negative given the electrostatic attraction between positive GFP and negatively-charged surfaces of the ribosomes . The second phenomenon we explain is the relation between Deff and the surface charge of GFP . In the work describing the hirudin-thrombin interaction a number of charge variants of hirudin were used ( Stone et al . , 1989 ) . The ΔGio0 ∘depended linearly on the number of charges . This is expected from Coulombs law , assuming that non-linearities do not arise from charge screening . In the rest of the analysis we assume that ΔGio0 ∘indeed depends linearly on the charge and we write: ΔGio0 ∘=ΔGpc ∘×charge , where ΔGpc ∘is the free energy change per charge . We can now combine this with Equations ( 1 ) , ( 2 ) , ( 3 ) , and ( 4 ) to obtain: ( 5 ) Deff= ( 1−[binding site][binding site]+eΔGnio∘+ΔGpc ∘chargeexp ( −C1I ) 1+C1IRT ) ( Dfree−Dbound ) +Dbound We used this equation to fit the data for E . coli and Hfx . volcanii . We set Dfree = 10 µm2/s , Dbound = 0 . 04 µm2/s ( ribosome diffusion coefficient ) , [binding site] = 660 µM , T = 293 K , R = 8 . 314 J K−1 mol−1 ( gas constant ) , and I = 0 . 2 M for E . coli and I = 2 . 1 M for Hfx . volcanii . We are left with three fitting parameters: ΔGnio∘ , ΔGpc ∘ , and C1 . The fits are shown in Figure 6d and e ( see Supplementary file 1D for fitting parameters ) . The model fits the data well; this is more telling for E . coli than it is for Hfx . volcanii , as the data covers more of the curve . The upper bound for the diffusion coefficient is set by free diffusion and the lower bound by the diffusion of the ribosome . When we use a log scale to represent the diffusion coefficient we see a linear dependence of diffusion coefficient with net charge from 0 to +25 ( for E . coli ) . Thus , under the assumption that ΔGio0∘ depends linearly on the number of charges the model reproduces the linear dependence between the upper and lower bound . Again , we needed to include a non-ionic interaction for a proper fit . There is a discrepancy between the parameter values of the fits shown in Figure 6b , d and e ( see Supplementary file 1D ) . This may be caused by the assumptions made above not holding up . Together the results for the relation between Kd and ionic strength , and Deff and GFP charge , show that the binding of GFP to ribosomes can be described by electrostatic interactions and screening by small ions on top of a base non-ionic interaction component . To determine the consequences of our findings we analyzed the proteomes of E . coli , L . lactis and Hfx . volcanii and four ( endo ) symbiotic bacteria . We determine ( i ) how a protein will diffuse in light of the composition of the proteome , for which we need to know both the net charges and the abundances of all proteome components; and ( ii ) how the ribosomes affect the diffusion of the proteome constituents , for which we need to know the net charge of the proteins . We determined the distributions of pI values and net charges for all proteins in the genome and for only cytoplasmic proteins , in E . coli , L . lactis and Hfx . volcanii ( Figure 7a ) . We also determined the distribution of pI values and net charges for cytoplasmic proteins in E . coli taking into account protein copy numbers ( Figure 7—figure supplement 1 ) . From the pI distributions it is clear that in all three organisms the majority of cytoplasmic proteins is acidic and thus negatively charged at the physiological internal pH of 7 . 5; for internal pH values we refer to ( Slonczewski et al . , 1981; Zilberstein et al . , 1982; Wilks and Slonczewski , 2007 ) for E . coli ( see also BNID 105980 and BNID 106518 ) ( Milo et al . , 2010 ) , and ( Poolman et al . , 1987 ) for L . lactis . The protein net charge distributions of E . coli and L . lactis go up to a value of +25 , irrespective of whether we take the gene-based distributions or protein copy numbers ( for E . coli ) , or whether we take the full or cytoplasmic proteome . The net charge distribution of Hfx . volcanii stops at about 0 . In E . coli 35 cytoplasmic proteins have a net charge higher than +10 . These consist of 18 ribosomal , 9 RNA-associated , 5 DNA-associated and 3 uncharacterized proteins . For L . lactis , with seven cytoplasmic proteins that have a net charge bigger than +10 , the breakdown is similar . The only Hfx . volcanii protein with a net charge bigger than 0 is a ribonuclease , rnp4 , with a net charge of +6 . Thus , all three organisms essentially have no ‘free’ positive cytoplasmic proteins . The drop in diffusion coefficient with increased positive charge may partly explain why the proteome is mostly negative in E . coli , L . lactis and Hfx . volcanii . Positive proteins not only diffuse slowly but their binding to ribosomes might also inhibit protein synthesis , that is , by affecting the assembly or the activity of ribosomes . As mentioned , there are 18 ribosomal proteins in E . coli that have a net charge of more than +10 . If the findings on GFP are transferable to ribosomal proteins , then these ribosomal proteins experience a drop in diffusion coefficient of more than 5-fold . The most extreme cases , RplT and RplB , with net charges of +24 and +31 , would have a drop in diffusion coefficient of 100-fold . The fact that ribosomal proteins themselves are positively charged potentially limits the rate of assembly of new ribosomes . The reason is that ribosomal proteins that have just been synthesized bind nonspecifically to the surfaces of fully assembled ribosomes , and this causes slow diffusion , lower effective protein concentrations and may affect the functioning of ribosomes . An implication of our findings is that the synthesis of cationic ribosomal proteins and the assembly of ribosomes should be highly coordinated and preferably be modular to minimize unwanted side-effects of nonspecific interactions ( Davis et al . , 2016 ) . A high positive net charge is not a guarantee for binding to the ribosome . One could imagine a positive protein that is disordered before binding but ordered upon binding . The reduction in entropy reduces the binding affinity , which in turn causes the diffusion coefficient to be high . Another option is that the surface shapes don’t match even if the net charges are complementary . This would also lower the affinity and increase the diffusion coefficient . A conundrum is encountered when we look at the proteomes of the bacteria Buchnera aphidicola , Blochmannia floridanus , Onion yellows phytoplasma , and Wigglesworthia glossinidia brevipalpis . All four organisms are ( endo ) symbionts of plants or insects and have small genomes: 572–730 protein-encoding genes . All of these have very basic proteomes ( Figure 7b and Figure 7—figure supplement 2 ) . It is unclear how these organisms are able to deal with , or avoid , slow diffusion and ribosomes getting swarmed with positive proteins . A protein can diffuse only as slow as the combination of this protein and the slowest component it binds to in the cell . This is described by Equation ( 1 ) , which can be rewritten in the following way: ( 6 ) Deff= ffree ( Dfree− Dbound ) + Dbound If we fill in ffree = 0 we get Deff= Dbound and if we fill in ffree = 1 we get Deff= Dfree; the black lines in Figure 8 . If we fill in Dbound = 0 we get Deff= ffree Dfree , i . e . after some point Deff becomes independent of Dbound; this is illustrated by the grey lines in Figure 8 . In more concrete terms: 99% binding of +25 GFP to ribosomes ( Dribo=0 . 04 µm2/s ) leads to the same diffusion coefficient as 99% binding to DNA ( DDNA=0 . 000035–0 . 00007 µm2/s ) . We find that the diffusion coefficients of proteins in the cytoplasm of E . coli depend on their net charge and the distribution of charge over the protein surface , with positive proteins moving up to 100-fold slower . The diffusion becomes even slower when cells are exposed to an osmotic upshift . In L . lactis and Hfx . volcanii the slowdown in diffusion with increasing positive surface charge is less than in E . coli due to electrostatic screening . The decrease in diffusion coefficient is mainly caused by binding of positive proteins to ribosomes , with KD values on the order of µM; this shows that non-selected interactions need not be weak . Ribosome surface properties may thus limit the composition of the cytoplasmic proteome . These findings are of general value due to the universal presence of ribosomes in cells . Application of these findings to bacterial ( endo ) symbionts lays bare a paradox in the functioning of these cells .
We use E . coli strain MG1655 ( Blattner et al . , 1997 ) . The GFP variants , −30 , –7 , 0 , +7 , +11a , +11b , +15 , and +25 , were all expressed from an L-arabinose inducible promoter on a pBAD vector with an ampicillin-resistance selection marker . We obtained the genes for −30 , –7 , +15 , and +25 from David Liu’s lab at Harvard , and nucleotide sequences of +7 , +11a , +11b from David Thompson . See ( McNaughton et al . , 2009 ) for −30 , –7 , +15 , and +25 GFP; see ( Thompson et al . , 2012a ) for +7 , +11a and +11b . We designed the 0 GFP ourselves . All GFP variants have an N-terminal histag . For all GFP variants amino acid sequences are available in Supplementary file 1A . We used Lactococcus lactis strain NZ9000 ( Linares et al . , 2010 ) , which contains the nisR and nisK genes which in the presence of the inducer , nisin A , switches on the expression of genes from the nisA promoter ( Kuipers et al . , 1998 ) . We cloned the coding segments for the his-tagged versions of −30 , −7 , +15 and +25 GFP behind the nisA promoter in the pNZ8048 vector ( Kuipers et al . , 1998 ) . The expression levels of −30 GFP were too low for FRAP analysis . We used Hfx . volcanii strain H1895 ( Strillinger et al . , 2016 ) . We expressed the GFP variants , −30 , –7 , +15 , and +25 , from the pTA1228 plasmid , which has a tryptophan-inducible promoter ( Brendel et al . , 2014 ) . The amino acid sequences are the same as for E . coli and L . lactis . We optimized the nucleotide sequence for Hfx . volcanii by making the codon frequency in the GFP variants the same as for protein coding genes on the Hfx . volcanii chromosome . We constructed the pTA1228 bearing the genes for GFP variants in E . coli , and transformed the final plasmids in Hfx . volcanii by protocols described in the Halohandbook ( Holmes et al . , 2008 ) . We obtained the strain , plasmid and the codon usage table from Thorsten Allers ( University of Nottingham , UK ) . For each experiment we took a glycerol stock of E . coli with one of the GFP variants and stabbed it with a pipette tip to obtain a small amount of cells . These we deposited in 4 mL LB medium containing 0 . 2 % v/v glycerol and 100 µg/mL ampicillin . We incubated the culture at 30°C , with 200 rpm shaking . The next day we took 8 µL of the LB culture to inoculate 4 mL MBM containing 0 . 2 % v/v glycerol and 100 µg/mL ampicillin . The composition of MBM , MOPS based medium , can be found in ( Neidhardt et al . , 1974 ) . We adjusted the osmolality of MBM to 0 . 28 Osm with NaCl . Osmolalities were measured with an Osmomat 030 cryoscopic osmometer ( Gonotec , Berlin , Germany ) . For the −30 GFP variant we also added 0 . 4% L-arabinose ( from a 20 % w/v stock in MilliQ ) , to induce protein expression . Again we incubated at 30°C , with 200 rpm shaking . The next morning the cultures had reached an OD600 between 0 . 6–1 . 6 , which were diluted to an OD600 of 0 . 18–0 . 25 . At the moment of dilution we also induced the expression of −7 GFP , with 0 . 1 % w/v L-arabinose , and 0 , +7 and +11b GFP , with 0 . 4 % w/v L-arabinose . We incubated the cultures for a further 2–4 hr , to obtain an OD600 of 0 . 4–0 . 5 , and then performed the FRAP measurements . To avoid aggregation , the +11a , +15 and +25 GFP variants were induced with 0 . 4 % w/v L-arabinose 1–2 hr before the FRAP measurements . For each GFP variant the experiment was repeated at least three times . For each experiment we took a glycerol stock from the −80°C freezer and stabbed it with a pipette tip to obtain a small amount of cells . These cells were deposited in 4 mL of growth medium in a culturing tube . The growth medium was CDM in all cases; the formulation of the chemically defined medium ( CDM ) is given in the supplement of ( Mika et al . , 2014 ) , where it is referred to as CDMRP . There is one difference , here we also added L-proline ( 0 . 68 g/L , final concentration ) . We include glucose ( 1 % w/v ) , as a carbon and energy source , and chloramphenicol ( 5 µg/mL ) , to maintain the plasmids . We incubated the cultures at 30°C , without shaking ( L . lactis grows semi-anaerobically ) . In the morning of the next day about 100 uL of culture was added to 4 mL of fresh CDM , to yield an OD600 of about 0 . 1 . Simultaneously , we added 4 uL of nisin A solution ( filtered supernatant from a L . lactis NZ9700 culture ) . The cultures were incubated at 30°C . We used the cultures for FRAP measurements at an OD600 of 0 . 38–0 . 46 . We diluted the cultures to keep them from overgrowing . For each GFP variant the experiment was repeated 2–3 times . For each experiment we took 2–3 colonies of Hfx . volcanii , expressing −30 , –7 , +15 , or +25 GFP , from an Hv-YPC agarose plate and suspended these in 4 mL Hv-YPC medium ( Holmes et al . , 2008 ) . We incubated the cultures at 42°C , with 200 rpm shaking . The next morning we diluted the culture to an OD600 of 0 . 2–0 . 3 and at the same time added 4 mM L-tryptophan , to induce expression of the GFP variants . We incubated the cultures for 2–3 hr at 42°C , with 200 rpm shaking , before using the cells for FRAP measurements . At the time of the measurements the OD600 was 0 . 3–0 . 5 . For each GFP variant the experiment was repeated three times . We performed fluorescence recovery after photo-bleaching ( FRAP; see Figure 1a , b ) on a LSM710 Zeiss confocal laser scanning microscope ( Zeiss , Oberkochen , Germany ) , following a method originally described in ( Elowitz et al . , 1999 ) . Our implementation of this method is described in ( Mika et al . , 2014 ) . We started with an overview image containing many cells , from which picked cells that are lying flat , are not undergoing cell division and have no neighbors that would obscure the analysis . We take a high resolution close-up of the cell and its immediate surroundings to see if the cell is fit for measurements . For FRAP we programmed the microscope to take three images , then photo bleach the GFP at one of the cell poles and finally record the recovery of the fluorescence over time . We recorded all images with a 488 nm laser; the same laser was used for bleaching but at a higher power . For E . coli we did the FRAP measurements as follows . We took 400 µL culture and resuspended those cells twice in 300 µL MBM* . MBM* did not have glycerol or ampicillin and has Na+ instead of K+ . The osmolality of the MBM* was either 0 . 28 , 0 . 55 or 1 . 2 Osm . We adjusted the osmolality of the resuspension medium with NaCl . After we resuspended the cells we pipetted 4 µL of these cells on a cover slide . To make sure the E . coli cells didn’t move we used ( 3-aminopropyl ) triethoxysilane ( APTES ) -treated cover slides . The slides were prepared as follows . First we cleaned them by sonicating for 1 hr in 5 M KOH , rinsing 10 times with MilliQ and blowing off the remaining MilliQ with pressurized nitrogen . We then deposited the slides in acetone that contained 2 % v/v ( 3-aminopropyl ) triethoxysilane . We incubated for 5 min at room temperature , removed the acetone and APTES and rinsed the slides 10 times with MilliQ . Again , the remaining MilliQ was blown off with pressurized nitrogen . After putting our cells on the APTES slide we put an object slide on top , for stability , and put the whole on the microscope stage . The stage temperature was maintained at 30°C . We used the slide for no longer than 20 min after depositing the cells . For −30 , –7 and 0 GFP under normal conditions , that is , no osmotic upshift , we recorded images at 50 time points and with 8 × 8 pixels , with a 4 ms exposure time and no extra time between exposures . For the positive GFP variants , and for the FRAP experiments after osmotic upshift ( slower diffusion ) , we recorded images at a 100 time points , with 16 × 16 pixels , and a 8 ms exposure and a 8–100 ms time step between the start subsequent exposures . For L . lactis we pipetted 4 uL culture on a cover slide . We put an object slide on top , for stability , and the whole was put on the stage of the microscope ( maintained at 30°C ) . We made sure that the cells didn’t move by using cover slides that were sonicated for 1 hr in 5 M KOH , rinsed 10 times with MilliQ and dried by blowing of the remaining MilliQ with pressurized nitrogen . We used cover slides for no longer than 20 min after depositing cells , and cultures for no longer than 1 hr after reaching an OD600 of 0 . 38–0 . 46 . We recorded the images in 8 × 10 pixels and with an exposure time of 5–37 ms , short for −7 GFP and long for +25 GFP . For each cell we recorded the whole FRAP measurement in 50 images , without extra time between exposures . For Hfx . volcanii we pipetted 4 µL culture on a cover slide ( non-treated ) . Then a patch of 1% agar in 18% SW was put on top , to immobilize the cells ( see the Halohandbook ( Holmes et al . , 2008 ) for the composition of SW ) . We then put the sample on the microscope stage . The stage temperature was maintained at 30°C . After a couple of minutes the cells stopped moving and we performed our FRAP measurements . We imaged for 20 min on a single sample . We recorded the images in 16 × 16 pixels with an exposure time of 8 ms and a time step , the time between the start of subsequent exposures , of 8–20 ms . For +15 and+25 GFP we see clear aggregates in some cells ( Figure 2—figure supplement 1a ) . We did not include these cells in the FRAP measurements . Overall about 10% of the analyzed cells were too noisy and/or did not show a bleached area , so that a diffusion coefficient could not be determined . Those cells were excluded from the analysis . For the FRAP results of −30 GFP ( 1 . 2 Osm shock ) , −7 GFP and 0 GFP in E . coli we excluded around 20% of the cells . For 0 GFP this was necessary because the fluorescence level was too low in a fraction of the cells; for −30 ( shock ) and −7 GFP the apparent diffusion was too fast for detection . When we include the excluded cells we obtain the following medians: 0 . 28 µm2/s for −30 GFP ( shock ) , 11 . 3 µm2/s for −7 GFP and 9 . 8 µm2/s for 0 GFP . This can be compared to the values 0 . 18 , 10 and 8 . 6 µm2/s reported in Supplementary file 1B . We grew E . coli , containing +25 GFP , in a culturing tube with 4 mL EZ; a rich defined growth medium ( Teknova , Hollister , CA , USA ) , to which we added glycerol ( 0 . 2 % v/v ) , as a carbon and energy source , and ampicillin ( 100 µg/mL ) , to maintain the plasmid . We used EZ medium because the chloramphenicol didn’t condense the DNA in cells grown in MBM . The culture was incubated at 30°C , with 200 rpm shaking for aeration . The next morning we used 200 uL of this culture to inoculate 4 mL of fresh EZ medium . We incubated the culture for 1 hr before adding 0 . 1% ( w/v ) L-arabinose , to induce the expression of +25 GFP . After another hour of incubation , at an OD600 of 0 . 5–0 . 6 , we added DRAQ-5 ( 2 µM ) , to visualize the DNA , and chloramphenicol ( 200 µg/mL ) , to condense the DNA ( Bakshi et al . , 2012; Chai et al . , 2014 ) . We imaged these cells between 1 and 1 . 5 hr after adding the DRAQ-5 and chloramphenicol , for which we deposited 10 uL culture on an APTES cover slide , prepared as described above , put an object slide on top and put the whole on the microscope stage . We performed all measurements at 30°C . We focused on a 200 µm x 200 µm area , containing ~200 cells , and recorded an image in the 488 ( +25 GFP ) and 633 ( DNA ) channels and used an exposure time of 3 . 3 s . We also recorded the transmitted excitation light to obtain a bright-field image . We picked the cells used for analysis from the transmission image to avoid bias . We selected cells that were lying flat and in focus . We did FRAP measurements on −7 and +25 GFP in DNA free regions in E . coli . The cells were grown in a culturing tube with 4 mL LB medium , containing glycerol ( 0 . 2 % v/v ) , as a carbon and energy source , and ampicillin ( 100 µg/mL ) , to maintain the plasmid . We incubated the culture overnight at 37°C , with 200 rpm shaking . We used LB medium , and incubated at 37°C , to get elongated cells in a reasonable time window upon cephalexin treatment ( see below ) . The next day we made two new cultures , 4 mL LB ( same composition as above ) , by adding 4 µL or 16 µL of overnight culture . We incubated these cultures at 37°C , with 200 rpm shaking . At an OD600 between 0 . 19–0 . 26 we added L-arabinose ( 0 . 1–0 . 2 % w/v ) , to induce GFP expression , and cephalexin ( 25 µg/mL ) , to elongate the cells ( Chai et al . , 2014 ) . After a further two hours of incubation we added chloramphenicol ( 200 µg/mL ) , to condense the DNA ( Chai et al . , 2014 ) , and DRAQ-5 ( 10 µM ) , to stain the DNA . The concentration of DRAQ-5 is above the minimum inhibitory concentration , 5 µM , for growth of E . coli MG1655 in EZ medium ( Bakshi et al . , 2012 ) ; at lower concentrations of DRAQ-5 the DNA did not stain properly . After a further 30–70 min incubation we took 200–400 µL of culture and resuspended the culture twice in 200 µL LB ( with 0 . 2 % v/v glycerol , 100 µg/mL ampicillin and 200 µg/mL chloramphenicol ) , to get rid of the DRAQ-5 background fluorescence . We used the following stock solutions: 20 % w/v L-arabinose in MilliQ , 1 mg/mL cephalexin in MilliQ , 20 mg/mL chloramphenicol in ethanol , and 200 µM DRAQ-5 in MilliQ . We deposited 4 µL of the sample on an APTES cover slide , put an object slide on top and put the whole on the microscope stage . The microscope stage temperature was maintained at 37°C . The cells were on the stage for no longer than 1 hr . We measured the diffusion coefficients of −7 and +25 GFP in these treated cells by the same method as before . The exception is that we do not draw the line for FRAP analysis from pole to pole . We draw it either to where DNA blocks movement of GFP ( see Figure 4—figure supplement 2a ) or far enough away from the bleach . It is important that the boundary conditions that are used in the analysis are still satisfied , meaning no transfer of particles over the ends of the line . We also make sure to only measure at places where there is no DNA present . We recorded the recovery in 150 time points with 750 ms exposure time for +25 GFP and 23–30 ms for −7 GFP . There was no additional time between exposures . The experiment was performed twice for both −7 and +25 GFP . We performed FRAP measurements over time of +25 GFP expressing E . coli cells with and without rifampicin treatment . The cells were grown in a tube with 4 mL LB ( with 0 . 2 % v/v glycerol and 100 µg/mL ampicillin ) . We incubated the culture overnight at 30°C , with 200 rpm shaking . The next day we used 8 µL of the overnight culture to inoculate a 4 mL MBM culture ( with 0 . 2 % v/v glycerol and 100 µg/mL ampicillin ) . Again we incubated the culture at 30°C , with 200 rpm shaking . The next morning , depending on the OD600 , the cultures were diluted with more MBM or allowed to continue growing . When the culture reached an OD600 of 0 . 17–0 . 23 the production of +25 GFP was induced by adding 0 . 4 % w/v L-arabinose ( from a 20 % w/v in MilliQ stock ) . At OD600 of 0 . 30–0 . 34 we took 198 µL culture and added either 2 µL DMSO ( control ) or 2 µL DMSO with 50 mg/mL rifampicin ( for a final concentration of 0 . 5 mg/mL ) . After mixing we deposited 4 µL sample on an APTES cover slide , put an object slide on top and the put the whole on the microscope stage . The stage was maintained at 30°C for the duration of the experiment . We measured the diffusion coefficients by FRAP and recorded the time for each measurement . We did each FRAP measurement on a unique cell . The replicates represent separate cultures on the day of the FRAP measurements . For each experiment on E . coli cell lysates , with E . coli expressing either −7 or +25 GFP , we deposited a small amount of cells from a glycerol stock into 4 mL LB medium ( containing 0 . 2 % v/v glycerol and 100 µg/mL ampicillin ) . We incubated the cultures at 30°C with 200 rpm shaking overnight . The next day we took 20 µL of the LB culture to inoculate 10 mL MBM ( 0 . 28 Osm , osmolality adjusted with NaCl , containing 0 . 2 % v/v glycerol and 100 µg/mL ampicillin ) . Again we incubated overnight . The next morning the cultures had reached an OD600 between 0 . 8–1 . 3 , and were diluted to an OD600 of 0 . 1–0 . 16 in 50 mL of fresh medium in a 250 mL flask . We added 0 . 4% ( w/v ) L-arabinose to induce protein expression . We incubated the cultures for 3 . 5–4 hr , to obtain an OD600 of 0 . 25–0 . 37 . We centrifuged 44 mL of each culture at 5250 g , 20 min , 4°C . From this point onward we did all the work on ice and used cooled buffers . Pellets were suspended in 1 mL of resuspension buffer ( 20 mM Tris-HCl pH 7 . 5 , 15 mM magnesium acetate , 100 mM ammonium acetate plus 6 mM 2-mercaptoethanol ) , resulting in around 200–300 fold dilution of cytoplasmic content . To calculate the dilution we assumed a cytoplasmic volume 0 . 5 fL ( Taheri-Araghi et al . , 2015 ) and 8 × 108 cells in 1 mL of culture of OD600 of 1 . To each tube containing the suspension we added around 0 . 2 mg of 106 μm glass beads ( Sigma , St . Louis , MO , USA ) and lysed the cells using two repetitions of 50 Hz oscillation for 5 min ( TissueLyser LT , QIAGEN , Venlo , The Netherlands ) . We cooled the sample on ice in between repetitions . We added PMSF ( 100 mM in isopropanol stock ) to the lysates to a final concentration of 1 mM . Then the lysates were centrifuged at 9000 g , for 2 min at 4°C . We took the supernatant and centrifuged it at 9000 g for 15 min at 4°C . We layered 800 μL of the resulting supernatant onto 8 mL of linear 10–40% sucrose gradient . The sucrose solutions contained 1 mM PMSF and were prepared with the resuspension buffer . We centrifuged the gradients using a swing-out rotor ( SW 32 . 1 Ti , Beckman , Brea , CA , USA ) at 125 000 g for 80 min at 4°C as described previously ( Maki et al . , 2000; Puri et al . , 2014 ) . We recorded a fluorescence profile over the sucrose gradient by dividing the gradient in 600 μL fractions , and measuring the fluorescence intensity for each fraction in a Jasco FP-8300 fluorimeter . We excited with 488 nm and recorded the emission from 500 to 600 nm ( in 5 nm intervals ) . For the analysis we used the fluorescence emission at 510 nm . To correct for background fluorescence , we acquired spectra of 10 , 20 , 30% and 40% sucrose in resuspension buffer with 1 mM PMSF . A linear fit of the 510 nm emission intensities was used to calculate sucrose-caused background values for each fraction . For lysates of E . coli expressing −7 and +25 GFP the experiment was carried out two times . For the samples containing DNA , we dissolved salmon testes DNA in autoclaved MQ to a final concentration of 1 mg/mL . The DNA was added to the cell lysates directly after the second centrifugation step; the sample was incubated for around 30 min on ice , before layering it onto the sucrose gradient . To determine the fractionation profile of DNA we layered 0 . 2 mg/ml DNA onto the linear sucrose gradient , except that the 2-mercaptoethanol and PMSF were omitted . The collected fractions were diluted 1:1 in 20 mM Tris-HCl pH 7 . 5 , 15 mM magnesium acetate , 100 mM ammonium acetate . We determined DNA levels by measuring the absorbance of each fraction from 200 to 340 nm with 5 nm intervals , using Cary 100 Bio UV-VIS spectrometer . To correct for background absorption we measured fractions of pure MQ sample treated in the same way . For lysates of E . coli expressing +25 GFP with addition of DNA the experiment was carried out once for each DNA concentration; the DNA control experiment was also done once . We dialyzed the fractionated cell lysate samples in pre-cooled 20 mM Tris-HCl pH 7 . 5 , 15 mM magnesium acetate , 100 mM ammonium acetate for 1 hr to remove the sucrose . The samples were pipetted on glow-discharged carbon-coated copper grids , excess liquid was removed by blotting and the grids were stained with 2% uranyl acetate . EM was performed on a Tecnai T20 electron microscope ( FEI , Eindhoven , The Netherlands ) operated at 200 kV , images were acquired with a 4000 SP 4K slow-scan CCD camera ( Gatan , Pleasanton , CA , USA ) as described previously ( Puri et al . , 2014 ) . The protocol for isolating ribosomes is based on ( Blaha et al . , 2000 ) and ( Moazed et al . , 1986 ) . For the isolation of ribosomes we used E . coli MC1061 cells . These cells harbor a pBAD vector ( Fulyani et al . , 2013 ) . A small amount of cells from a glycerol stock was deposited into 30 mL of LB medium containing 100 µg/mL ampicillin in a 100 mL flask . We incubated the cultures at 37°C overnight with 200 RPM shaking . The next day we inoculated two cultures of 1 L fresh medium in 5 L flasks with 10 mL of the overnight culture each . We grew the cultures for 2–3 hr , until an OD600 of 0 . 66–0 . 81 . We centrifuged the cultures at 6000 g , 10 min , 4°C in a JLA-9 . 1000 rotor ( Beckman ) . From this point onward we did all the work on ice and used cooled buffers . Pellets were suspended in 10–20 mL of resuspension buffer ( 20 mM HEPES-NaOH pH 7 . 5 , 10 mM MgCl2 , 30 mM ammonium acetate , 150 mM KCl , 10 mM NaCl , 6 mM 2-mercaptoethanol , 1 mM PMSF ) . About 10 µg/mL of DNase I ( Sigma ) was added to the cell suspension . Cells were lysed by sonication for 12 min with cycling on and off every 5 s . We used the Vibra-Cell VCX 130 sonicator ( Sonics , Newtown , CT , USA ) with 6 mm diameter probe at 70% amplitude , and we cooled the tube in an ethanol-ice bath . The lysates were centrifuged at around 30 , 000 g , 1 hr , 4°C in a MLA-80 rotor ( Beckman ) . The top part of the supernatant ( 4 out of 6 mL in the tube ) was carefully pipetted into clean centrifugation tubes . The supernatant was centrifuged at around 110 , 000 g , 17 hr , 4°C in a MLA-80 rotor . We discarded the supernatant , leaving an opaque , white-yellowish pellet . The pellet was washed gently with 1 mL of SEC buffer ( 20 mM HEPES-NaOH pH 7 . 5 , 10 mM MgCl2 , 30 mM ammonium acetate , 150 mM KCl , 10 mM NaCl , 6 mM 2-mercaptoethanol ) . Then , we gently added 0 . 8–1 . 6 mL of SEC buffer onto the pellet and nutated for 1 hr at 4°C . The resulting suspension was centrifuged at 20 , 000 g , 7 min , 4°C to pellet the aggregates . We purified the resulting supernatant on a SEC setup ( AKTA , GE Healthcare , Chicago , IL , USA , equipped with 1260 Infinity FLD fluorescence detector , Agilent , Santa Clara , CA , USA ) , using a Superdex 200 10/300 GL ( GE Healthcare ) column and SEC buffer as eluent . Three peak A280 fractions were pooled , resulting in 1 . 5 mL of purified ribosomes . We measured absorbance at 260 and 280 nm , using a NanoDrop ND-1000 ( Thermofisher , Waltham , MA , USA ) spectrophotometer . Reported A280 values varied between 0 . 27 and 1 . 08 at 1 mm light path , depending on the replicate , the amount of buffer used for resuspension of the ribosome pellet and the volume loaded into the SEC setup . A260/A280 ratio of replicates was constant at around 1 . 9 . From now on , all mentioned absorbance values are reported with a 1 mm light path . The protocol for isolating −7 and +25 GFPs is based on ( Thompson et al . , 2012b ) . For the purification of GFPs we used E . coli MG1655 strains containing pBAD bearing the gene for either −7 or +25 GFP . We deposited a small amount of cells in 30 mL of LB with 100 µg/mL ampicillin in a 100 mL flask for −7 GFP , and in 100 mL of medium in a 500 mL flask for +25 GFP . The cultures were incubated at 37°C overnight with 200 RPM shaking . The next day we inoculated 2 L and 6 L of fresh medium for −7 and +25 GFP , respectively , by adding 10 mL of overnight culture to 1 L of medium in a 5 L flask . At the time of inoculation , the protein expression was induced by adding L-arabinose to final concentration of 0 . 4 % w/v . We incubated the cultures at 30°C , 200 RPM for about 3 hr . We centrifuged the cultures at 6000 g , 10 min , 4°C in a JLA-9 . 1000 rotor . From this point onward we did all the work on ice and used cooled buffers . We suspended the pellets in GFP resuspension buffer ( 50 mM potassium phosphate pH 7 . 5 , 2 M NaCl , 1 mM MgCl2 , 20 mM imidazole ) at around 5–10 mL of GFP resuspension buffer per 1 L of culture . About 10 µg/mL of DNase I and about 10 µg/mL of RNase A ( Sigma ) were added to the cell suspension . Cells were lysed by sonication , for 12 min with cycling on and off every 5 s . We used Vibra-Cell VCX 130 sonicator ( Sonics ) , with 6 mm diameter probe at 70% amplitude , and cooled the tube in an ethanol-ice bath . Immediately after the sonication , we added EDTA to a final concentration of 0 . 5 mM . We centrifuged the lysate at around 20 , 000 g , 20 min , 4°C in a JA-25 . 50 rotor ( Beckman ) . We collected the supernatants and added Ni Sepharose 6 Fast Flow ( GE Healthcare ) resin , corresponding to 2 mL of column volume , to +25 and −7 GFP isolates each . The supernatants with the column material were nutated for 45 min at 4°C . Then we put the suspensions into columns , and washed each with 20 column volumes of GFP equilibration buffer ( 50 mM potassium phosphate pH 7 . 5 , 2 M NaCl , 20 mM imidazole ) , then with 20 column volumes of GFP wash buffer ( 50 mM potassium phosphate pH 7 . 5 , 2 M NaCl , 50 mM imidazole ) . The proteins were eluted with GFP elution buffer ( 50 mM potassium phosphate pH 7 . 5 , 2 M NaCl , 500 mM imidazole ) , and around 1 mL of the highest intensity fractions were pooled . We then added EDTA to each pool to a final concentration of 5 mM . Purified −7 and +25 GFP were centrifuged at 20 , 000 g , 7 min , 4°C to pellet possible aggregates . We purified the resulting supernatant on a SEC setup ( GE Healthcare AKTA equipped with Agilent 1260 Infinity FLD fluorescence detector ) , using Superdex 200 10/300 GL ( GE Healthcare ) column and SEC buffer ( 20 mM HEPES-NaOH pH 7 . 5 , 10 mM MgCl2 , 30 mM ammonium acetate , 150 mM KCl , 10 mM NaCl , 6 mM 2-mercaptoethanol ) as running buffer . We pooled three fractions with the highest 510 nm emission at 488 nm excitation into 1 . 5 mL of purified GFP solution for −7 and +25 GFP each . We measured the absorbance at 280 nm , using a NanoDrop ND-1000 ( Thermofisher , Bleiswijk , NL ) spectrophotometer . Reported A280 values were around 0 . 015 for −7 GFP and 0 . 022 for +25 GFP , with little variation between replicates . Both −7 and +25 GFP solutions were visibly green . During preliminary experiments we noticed aggregation occurring while mixing +25 GFP with ribosomes at low dilution of the SEC purification pools . The aggregation was reproducible throughout all replicates . Despite the aggregation not being visible by naked eye , we were still able to see a pellet after centrifugation when imaging the fluorescence of the tubes ( Figure 5e ) . Through trial-and-error we established that mixing ribosomes at A280 = 0 . 14 and+25 GFP at A280 = 0 . 0013 results in no aggregation ( visible by naked eye after centrifugation at 20 , 000 g , 7 min , 4°C ) , while producing a peak at 280 nm for ribosomes when run again on SEC . For the main experiments ribosomes and GFPs were diluted in SEC buffer to A280 = 0 . 14 and A280 = 0 . 0013 , respectively , in a total volume of 0 . 8 mL . The solutions were then centrifuged at 20000 g , 7 min , 4°C to pellet aggregates . In the cases where we mixed ribosomes with −7 or +25 GFP , the GFP was added to the ribosome solution . The solutions were incubated on ice for 10 min before centrifugation . We collected the supernatant and ran 0 . 6 mL immediately on SEC ( GE Healthcare AKTA equipped with Agilent 1260 Infinity FLD fluorescence detector ) , using Superdex 200 10/300 GL ( GE Healthcare ) column and SEC buffer as running buffer , while monitoring absorption at 280 nm and emission at 510 nm with 488 excitation . The centrifugation tubes and remaining solution were imaged for fluorescence using the LAS-3000 ( Fujifilm , Tokyo , Japan ) imager . We performed all these measurements twice . Additionally , for +25 GFP we ran a ribosome/GFP mixture with a 1 . 8x higher GFP concentration ( A280 = 0 . 0024 ) that exhibited clear aggregation . We made histograms of the distributions of pI and net charge of all proteins encoded by the genomes of E . coli , L . lactis and Hfx . volcanii . All protein sequence data was retrieved from UniProt ( Bateman et al . , 2015 ) . For E . coli we used a K12 strain ( proteome ID: UP000000318 ) , for L . lactis we used strain MG1363 ( proteome ID: UP000000364 ) and for Hfx . volcanii we used strain DS2 ( proteome ID: UP000008243 ) . The L . lactis MG1363 strain is the parent strain of L . lactis NZ9000 that we used for FRAP ( Linares et al . , 2010 ) . The Hfx . volcanii DS2 is the parent strain of Hfx . volcanii H1895 ( Strillinger et al . , 2016 ) . We calculated the pI of each protein based on its amino acid sequence using the Isoelectric Point Calculator by Kozlowski ( Kozlowski , 2016 ) . We modified the program to allow for net charge calculations; the pI and net charge values we report are based on the IPC_protein pKa dataset of the Isoelectric Point Calculator . To calculate the net charge we used a pH of 7 . 5 . To get the distributions in the cytoplasm we took only those proteins that have gene ontology labels cytoplasm and cytosol in the uniprot database ( GO:0005737 and GO:0005829 ) . For E . coli this yielded 1406 proteins ( compared to 4254 proteins in the full genome ) , for L . lactis 253 ( 2383 ) , and for Hfx . volcanii 177 ( 3987 ) . For E . coli we also made pI and net charge distributions in which protein copy numbers are taken into account . To do this we took copy number data from Schmidt et al . ( Schmidt et al . , 2016 ) . Specifically , we took the abundance data for E . coli BW25113 cultured in M9 glycerol . We also made histograms of the distributions of pI and net charge of all proteins encoded by the genomes of Buchnera aphidicola ( proteome ID: UP000001806 ) , Blochmannia floridanus ( proteome ID: UP000002192 ) , Onion yellows phytoplasma ( proteome ID: UP000002523 ) , and Wiggleworthia glossinidia brevipalpis ( proteome ID: UP000000562 ) . For Buchnera the cytoplasmic fraction contained 190 proteins ( compared to 572 proteins in the full genome ) , for Blochmannia 156 ( 583 ) , for phytoplasma 87 ( 730 ) , and Wigglesworthia 158 ( 617 ) . To calculate the charge of the GFP variants we counted the number of Asp , Glu , Lys and Arg residues , used the pKa values of all ( de ) protonatable residues and used the Henderson-Hasselbalch equation to calculate the net charge . Results of these calculations give net charge 1–2 higher than net charge calculated using the modified IPC and the IPC_protein pKa dataset ( −31 . 1 , –8 . 2 , −1 . 3 , +5 . 6 , +9 . 5 , +9 . 5 , +13 . 6 , +23 . 5 for −30 , –7 , 0 , +7 , +11a , +11b , +15 and +25 GFP respectively ) . In reality , ions can specifically bind to proteins and thereby change the base net charge ( i . e . before any ionic screening effects occur ) ( Filoti et al . , 2015 ) . This is especially true for anions ( Filoti et al . , 2015 ) , which could affect our ( quantitative ) interpretation . Two examples: bovine serum albumin ( measured charge , −13 . 8; calculated charge , −18 . 3 ) ( Filoti et al . , 2015 ) and hen egg white lysozyme ( measured charge , +5 . 1; calculated charge , +11 ) ( Gokarn et al . , 2011 ) ; the actual values depend on the type ( s ) of ion ( s ) present ( Gokarn et al . , 2011 ) . We also assumed that each residue of a particular type ( e . g . all aspartates ) have the same pKa independent of context . To take ion binding and context dependent pKa values into account would be a whole study in itself . For diffusion in one dimension the probability density for the position of a particle after time , t , is given by: ( 7 ) p ( x ) = N4πDte−x24Dt Here x is the position , p ( x ) is the probability as a function of x , N is a normalization factor , D is the diffusion coefficient , and t is the time step . When the particle is free it moves with diffusion coefficient Dfree and when bound with Dbound . The particle goes back and forth between free and bound states a number of times in a certain period of time , Δt . Because the motion in each time step is independent of the other time steps , we can sum all time steps and distances travelled for the free state and we can do the same for the bound state . We end up with two equations like Equation 7 but in one we have D=Dfree and t = ffreeΔt and in the other D = Dbound and t = ( 1-ffree ) Δt , with ffree being the fraction of time that the particle is free . To get the probability density for the position of the particle after time step , Δt , we convolute the two equations . A convolution of a Gaussian function leads to another Gaussian in the following way: ( 8 ) f ( x ) ∗g ( x ) = N2πσfe−x22σf2∗N2πσge−x22σg2= N2π ( σf2+σg2 ) e−x22 ( σf2+σg2 ) Here , * , is the symbol for a convolution . By comparing Equations 7 and 8 we can see that σf2=2DfreeffreeΔt and σg2=2Dbound ( 1−ffree ) Δt . We can also define an effective diffusion coefficient , Deff , such that σf2+σg2= 2DeffΔt . Combining the last results and dividing by 2Δt we obtain Equation 1 . This derivation depends on six assumptions , as described in the discussion . The justification for these assumptions are as follows . We assumed that ( 1 ) the exchange between free and bound state is much faster than the FRAP measurement . This is justified because we did not observe two-component recovery in the FRAP data . We assumed that ( 2 ) the highest diffusion coefficient of all variants in a given organism reflects the free state of GFP; justified by the fact that for E . coli the GFP diffusion coefficient levels off towards more negative charge . We assumed that ( 3 ) GFPs bind solely to ribosomes; this we have shown experimentally . We assumed that ( 4 ) the total number of binding sites on all ribosomes is higher than the number of GFPs . The first justification is that the number of binding sites is about 106 and it is unlikely that we express that many GFPs because the cell only has about 3 × 106 total proteins . The second justification is that 99% of +25 GFP appears to be bound , meaning that there are enough binding sites to bind all GFPs . We assumed that ( 5 ) the decrease of diffusion coefficient with net positive charge has the same origin in all three organisms . This assumption is plausible because all three organisms have ribosomes , and assuming the same cause for slow diffusion is the most parsimonious . Finally , we assumed that ( 6 ) the ribosome diffusion coefficient is the same in all three organisms . Here the justification is that for all three organisms −7 GFP diffusion coefficients are similar , suggesting similar crowding , for E . coli and L . lactis the diffusion coefficient are similar also for a big protein complex ( Mika et al . , 2014 ) . The consequence for violating assumption one is that there is no Deff to speak of and the whole calculation becomes irrelevant . The consequence for violating assumptions 2 , 3 , 5 , and 6 is that the numerical values coming out of the equation will be different , with the severity of the error depending on the difference in diffusion coefficients . The consequence of violating assumption four is that there will be free GFP irrespective of affinity as there are no more binding sites to fill .
Much of the molecular motion in the cytoplasm is diffusive , which possibly limits the tempo of processes . We studied the dependence of protein mobility on protein surface properties and ionic strength . We used surface-modified fluorescent proteins ( FPs ) and determined their translational diffusion coefficients ( D ) in the cytoplasm of Escherichia coli , Lactococcus lactis and Haloferax volcanii . We find that in E . coli D depends on the net charge and its distribution over the protein , with positive proteins diffusing up to 100-fold slower than negative ones . This effect is weaker in L . lactis and Hfx . volcanii due to electrostatic screening . The decrease in mobility is probably caused by interaction of positive FPs with ribosomes as shown in in vivo diffusion measurements and confirmed in vitro with purified ribosomes . Ribosome surface properties may thus limit the composition of the cytoplasmic proteome . This finding lays bare a paradox in the functioning of prokaryotic ( endo ) symbionts .
Cells contain many proteins that constantly move about within the cell to carry out tasks that keep the cell running . A protein of average size makes contact with all the other proteins in a typical bacterial cell in a few seconds . This moving about mixes the cell’s contents , which is crucial for its survival and reproduction . Proteins can group together , or with other molecules , to form bigger units . This grouping together depends on the properties of protein surfaces; for example , opposite electrical charges on the surfaces of proteins can cause them to group together . Grouping together proteins causes them to move around cells more slowly . Indeed the ribosome , a protein unit that constructs new proteins and is found in every known species , moves over a hundred times more slowly than the average protein . Finding out how the total electric charge inside the cells of different species affects the mobility of proteins would give us a better idea of how fast tasks can be carried out in cells . Schavemaker , Śmigiel et al . now show that protein surface charge matters a great deal in the gut microbe Escherichia coli . In these cells , negatively charged and neutral proteins move about rapidly whereas positively charged proteins move up to 100 times more slowly . In the salt-loving microbe Haloferax volcanii the positive proteins move relatively fast , but still more slowly than negatively charged and neutral proteins . In all likelihood this is because the protein charges are shielded from each other by large amounts of small charged molecules ( which come from salts ) in the Hfx . volcanii cells . Schavemaker , Śmigiel et al . suggest that positively charged proteins slow down because they bind to negatively charged ribosomes . Because ribosomes are found in all living cells , understanding how they affect how other proteins move around the cell has a wide range of possible applications . For example , biologists and biotechnologists often produce proteins in E . coli for convenient study . Yet very positively charged proteins may bind to ribosomes in E . coli , causing experiments to fail . Using cells that shield charges better , such as Hfx . volcanii or Lactococcus lactis , could solve this issue .